<?xml version="1.0" encoding="UTF-8"?>
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    <title>sql</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/381/feed"/>
    <updated>2026-07-21T10:46:19+00:00</updated>
    <id>https://links.biapy.com/guest/tags/381/feed</id>
            <entry>
            <id>https://links.biapy.com/links/13325</id>
            <title type="text"><![CDATA[Knex.js]]></title>
            <link rel="alternate" href="https://knexjs.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13325"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Knex.js is a batteries-included SQL query builder for JavaScript.

Knex.js (pronounced /kəˈnɛks/) is a &amp;quot;batteries included&amp;quot; SQL query builder for PostgreSQL, CockroachDB, MSSQL, MySQL, MariaDB, SQLite3, Better-SQLite3, Oracle, and Amazon Redshift designed to be flexible, portable, and fun to use.

- [Knex.js @ GitHub](https://github.com/knex/knex).]]>
            </summary>
            <updated>2026-07-16T12:33:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13312</id>
            <title type="text"><![CDATA[Graphify]]></title>
            <link rel="alternate" href="https://graphify.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13312"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[the code knowledge graph for AI coding assistants.

Open-source and on-device. One command maps your repo into a graph your AI assistant traverses instead of grepping. Every answer traces to a path you can audit.

 AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph. 

- [Graphify @ GitHub](https://github.com/Graphify-Labs/graphify).]]>
            </summary>
            <updated>2026-07-15T12:00:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13304</id>
            <title type="text"><![CDATA[databow]]></title>
            <link rel="alternate" href="https://docs.columnar.tech/databow/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13304"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[databow is a command-line tool for querying databases.

A command-line tool for querying databases via ADBC.

- [databow @ GitHub](https://github.com/columnar-tech/databow).]]>
            </summary>
            <updated>2026-07-15T08:43:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13228</id>
            <title type="text"><![CDATA[Dqlite]]></title>
            <link rel="alternate" href="https://canonical.com/dqlite" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13228"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Embeddable, replicated and fault-tolerant SQL engine. 

Dqlite is a fast, embedded, persistent SQL database with Raft consensus that is perfect for fault-tolerant IoT and Edge devices. 

- [Dqlite @ GitHub](https://github.com/canonical/dqlite).

Related contents:

- [Hunting a 16-year-old SQLite bug with TLA+: is dqlite affected? @ Canonical Ubuntu Blog](https://ubuntu.com/blog/hunting-a-16-year-old-sqlite-bug-with-tla-is-dqlite-affected).]]>
            </summary>
            <updated>2026-07-06T12:03:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13197</id>
            <title type="text"><![CDATA[SQL to ER Diagram]]></title>
            <link rel="alternate" href="https://sqltoerdiagram.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13197"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Free Online SQL Diagram &amp;amp; ERD Generator.

 ER diagram generator. Paste CREATE TABLE statements and get a clean, interactive ERD — runs 100% in your browser, nothing uploaded 

- [SQL to ER Diagram @ GitHub](https://github.com/royalbhati/sqltoerdiagram).]]>
            </summary>
            <updated>2026-07-03T08:51:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13052</id>
            <title type="text"><![CDATA[actuallyEXPLAIN]]></title>
            <link rel="alternate" href="https://actuallyexplain.vercel.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13052"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Visual SQL Logic Mapper.

 actuallyEXPLAIN is a visualizer that helps you understand logical intent in complex PostgreSQL queries in a diagram and dictionarized form. 

- [actuallyEXPLAIN @ GitHub](https://github.com/freenandes/actuallyexplain).]]>
            </summary>
            <updated>2026-06-18T15:32:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/13021</id>
            <title type="text"><![CDATA[Tabularis]]></title>
            <link rel="alternate" href="https://tabularis.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13021"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source database client for PostgreSQL, MySQL/MariaDB and SQLite with SQL notebooks, visual EXPLAIN, AI and MCP built in. Hackable with plugins. 

Tabularis is an open-source desktop SQL workspace for PostgreSQL, MySQL/MariaDB, and SQLite, with a built-in MCP server so Claude, Cursor, and Windsurf can read your schema and run queries through the same app you already use.

- [Tabularis @ GitHub](https://github.com/TabularisDB/tabularis).]]>
            </summary>
            <updated>2026-06-15T06:05:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12830</id>
            <title type="text"><![CDATA[Coral]]></title>
            <link rel="alternate" href="https://withcoral.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12830"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your agent&amp;#039;s query language.
One SQL interface over APIs, files, and live sources — built for agents. 

Coral gives agents a local-first SQL runtime over APIs, files, and other data sources. Query it from the CLI, inspect schemas and tables, or expose the same runtime over MCP so agents can use it without bespoke tool glue.

- [Coral @ GitHub](https://github.com/withcoral/coral).]]>
            </summary>
            <updated>2026-05-25T06:18:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12822</id>
            <title type="text"><![CDATA[openHare]]></title>
            <link rel="alternate" href="https://sjjian.github.io/openhare/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12822"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI-powered desktop SQL client. Cross-platform. Built with Flutter. 

openhare is an AI-powered, cross-platform desktop SQL client with multi-database support, built for everyday development, data analysis, and DBA management workflows.

- [openHare @ GitHub](https://github.com/sjjian/openhare).

Related contents:

- [\#133 - News Juin 2026, Bun passe à Rust, npm verrouille les scripts et SEO pour l&amp;#039;IA @ Double Slash :fr:](https://double-slash.dev/podcasts/news-jun26/)]]>
            </summary>
            <updated>2026-06-04T05:51:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12767</id>
            <title type="text"><![CDATA[SQL Squid Game]]></title>
            <link rel="alternate" href="https://datalemur.com/sql-game" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12767"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[a free educational game that&amp;#039;s inspired by Netflix&amp;#039;s Squid Game, SQL Murder Mystery, and a few other SQL Games we love to play.]]>
            </summary>
            <updated>2026-05-15T13:49:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12647</id>
            <title type="text"><![CDATA[Rocky]]></title>
            <link rel="alternate" href="https://rocky-data.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12647"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A compiled SQL transformation engine in Rust. Type-safe compilation, column-level lineage, and an AI intent layer — for data pipelines that don&amp;#039;t break.

- [Rocky @ GitHub](https://github.com/rocky-data/rocky).]]>
            </summary>
            <updated>2026-04-29T13:15:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12590</id>
            <title type="text"><![CDATA[ggsql]]></title>
            <link rel="alternate" href="https://ggsql.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12590"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A SQL extension for declarative data visualisation based on the Grammar of Graphics. 

ggsql brings the elegance of the Grammar of Graphics to SQL. Write familiar queries, add visualization clauses, and see your data transform into beautiful, composable charts — no context switching, no separate tools, just SQL with superpowers.

- [ggsql @ GitHub](https://github.com/posit-dev/ggsql).]]>
            </summary>
            <updated>2026-04-21T11:38:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12405</id>
            <title type="text"><![CDATA[pGenie]]></title>
            <link rel="alternate" href="https://pgenie.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12405"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Write SQL. Ship confidence.
SQL-first tooling for PostgreSQL
Type-safe PostgreSQL client code generator.

pGenie validates SQL, manages indexes, and generates type-safe client SDKs — all derived from the migrations and queries in plain SQL. 

- [pGenie @ GitHub](https://github.com/pgenie-io/pgenie).]]>
            </summary>
            <updated>2026-04-03T16:43:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12126</id>
            <title type="text"><![CDATA[BIRD-bench]]></title>
            <link rel="alternate" href="https://bird-bench.github.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12126"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A BIg Bench for Large-Scale Relational Database Grounded Text-to-SQLs.

 BIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation) represents a pioneering, cross-domain dataset that examines the impact of extensive database contents on text-to-SQL parsing. BIRD contains over 12,751 unique question-SQL pairs, 95 big databases with a total size of 33.4 GB. It also covers more than 37 professional domains, such as blockchain, hockey, healthcare and education, etc. 

- [BIRD-SQL @ GitHub](https://github.com/AlibabaResearch/DAMO-ConvAI/tree/main/bird).

Related contents:

- [SQL Is Solved. Here&amp;#039;s Where Chat-BI Still Breaks @ Ju Data Engineering Newsletter](https://juhache.substack.com/p/sql-is-solved-heres-where-chat-bi).]]>
            </summary>
            <updated>2026-03-16T07:02:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11971</id>
            <title type="text"><![CDATA[SQL Crack]]></title>
            <link rel="alternate" href="https://github.com/buva7687/sql-crack" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11971"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Transform SQL queries into interactive visual flow diagrams.

SQL Crack is a VS Code extension that visualizes SQL queries as interactive execution flow diagrams. Understand complex queries at a glance, track data lineage across your entire workspace, and identify optimization opportunities with professional-grade visual analysis.]]>
            </summary>
            <updated>2026-03-02T06:53:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11904</id>
            <title type="text"><![CDATA[Shaper]]></title>
            <link rel="alternate" href="https://taleshape.com/shaper/docs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11904"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source, SQL-driven Data Dashboards powered by DuckDB.

Build analytics dashboards simply by writing SQL.

- [Shaper @ GitHub](https://github.com/taleshape-com/shaper).

Related contents:

- [Digest \#202: Terraform Claude Skills, FinOps FOCUS 1.2, AI Fatigue for Cloud Engineers, and MCP for Web Data Extraction @ DevOps Bulletin](https://www.devopsbulletin.com/p/digest-202-terraform-claude-skills).]]>
            </summary>
            <updated>2026-02-24T07:10:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11888</id>
            <title type="text"><![CDATA[sql-tap]]></title>
            <link rel="alternate" href="https://github.com/mickamy/sql-tap" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11888"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Watch SQL traffic in real-time with a TUI.
Real-time SQL traffic viewer — proxy daemon + TUI / Web client.

sql-tap sits between your application and your database (PostgreSQL, MySQL, or TiDB), capturing every query and displaying it in an interactive terminal UI. Inspect queries, view transactions, and run EXPLAIN — all without changing your application code. 

Related contents:

- [Newsletter du 16 Février 2026 @ Rudeops :fr:](https://www.rudeops.com/newsletter/2026-02-16-rudeops-newsletter/).]]>
            </summary>
            <updated>2026-02-20T13:35:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11879</id>
            <title type="text"><![CDATA[VillageSQL]]></title>
            <link rel="alternate" href="https://villagesql.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11879"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[VillageSQL is the Innovation Platform for MySQL.
A drop-in replacement for MySQL with extensions for the agentic AI era.

- [VillageSQL @ GitHub](https://github.com/villagesql/villagesql-server).

Related contents:

- [Introducing VillageSQL: A New Path for MySQL in the Agentic AI Era @ VillageSQL](https://villagesql.com/blog/introducing-villagesql/).
- [Roadmap: A new path for MySQL @ VillageSQL](https://villagesql.com/roadmap).
- [Extending MySQL with VillageSQL @ Max De Marzi](https://maxdemarzi.com/2026/05/21/extending-mysql-with-villagesql/).]]>
            </summary>
            <updated>2026-06-01T05:56:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11707</id>
            <title type="text"><![CDATA[sqldef]]></title>
            <link rel="alternate" href="https://sqldef.github.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11707"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Idempotent schema management for MySQL, PostgreSQL, SQLite, and SQL Server.

sqldef is a CLI tool for diffing two SQL schemas. You can use it to manage the migration of RDBMSs using regular SQL DDLs.

Supported databases: MySQL, MariaDB, TiDB, PostgreSQL, SQL Server, and SQLite3.

- [sqldef @ GitHub](https://github.com/sqldef/sqldef).]]>
            </summary>
            <updated>2026-02-05T12:43:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11665</id>
            <title type="text"><![CDATA[Text2SQirreL 🐿️]]></title>
            <link rel="alternate" href="https://github.com/distil-labs/distil-text2sql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11665"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Query your data in plain English.

Turn natural language questions into SQL queries with a small, local model that matches cloud LLM accuracy.

We fine-tuned a small language model to convert plain English questions into executable SQL queries. Because it&amp;#039;s small, you can run it locally on your own machine, no API keys, no cloud dependencies, full privacy. Load your CSV files, ask questions, get answers.]]>
            </summary>
            <updated>2026-02-02T06:33:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11421</id>
            <title type="text"><![CDATA[Apache Spark]]></title>
            <link rel="alternate" href="https://spark.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11421"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Unified Engine for large-scale data analytics.

Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. 

- [Apache Spark @ GitHub](https://github.com/apache/spark).

Related contents:

- [Introducing Apache Spark® 4.1 @ databricks](https://www.databricks.com/blog/introducing-apache-sparkr-41).
- [From Chaos to Scale: Templatizing Spark Declarative Pipelines with DLT-META @ databricks](https://www.databricks.com/blog/chaos-scale-templatizing-spark-declarative-pipelines-dlt-meta).
- [Breaking the Microbatch Barrier: The Architecture of Apache Spark Real-Time Mode @ databricks](https://www.databricks.com/blog/breaking-microbatch-barrier-architecture-apache-spark-real-time-mode).]]>
            </summary>
            <updated>2026-03-17T12:31:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11354</id>
            <title type="text"><![CDATA[SeaQuery]]></title>
            <link rel="alternate" href="https://www.sea-ql.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11354"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🔱 A dynamic SQL query builder for MySQL, Postgres and SQLite.

SeaQuery is a query builder to help you construct dynamic SQL queries in Rust. You can construct expressions, queries and schema as abstract syntax trees using an ergonomic API. We support MySQL, Postgres and SQLite behind a common interface that aligns their behaviour where appropriate. MS SQL Server Support is available under SeaORM X.

- [SeaQuery @ GitHub](https://github.com/SeaQL/sea-query).]]>
            </summary>
            <updated>2026-01-05T07:08:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11353</id>
            <title type="text"><![CDATA[Kysely]]></title>
            <link rel="alternate" href="https://kysely.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11353"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The type-safe SQL query builder for TypeScript.

Kysely (pronounce “Key-Seh-Lee”) is a type-safe and autocompletion-friendly TypeScript SQL query builder. Inspired by Knex.js. Mainly developed for Node.js but also runs on all other JavaScript environments like Deno, Bun, Cloudflare Workers and web browsers.

- [Kysely @ GitHub](https://github.com/kysely-org/kysely).

Related contents:

- [AI Is Forcing Us To Write Good Code @ Bits of Logic](https://bits.logic.inc/p/ai-is-forcing-us-to-write-good-code).]]>
            </summary>
            <updated>2026-01-05T07:05:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11349</id>
            <title type="text"><![CDATA[SQLFluff]]></title>
            <link rel="alternate" href="https://www.sqlfluff.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11349"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A modular SQL linter and auto-formatter with support for multiple dialects and templated code. 

SQLFluff is an open source, dialect-flexible and configurable SQL linter. Designed with ELT applications in mind, SQLFluff also works with Jinja templating and dbt. SQLFluff will auto-fix most linting errors, allowing you to focus your time on what matters.

- [SQLFluff @ GitHub](https://github.com/sqlfluff/sqlfluff).]]>
            </summary>
            <updated>2025-12-31T12:45:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11265</id>
            <title type="text"><![CDATA[sqlit]]></title>
            <link rel="alternate" href="https://github.com/Maxteabag/sqlit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11265"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A user friendly TUI for SQL databases. Written in python. Supports SQL server, Mysql, PostreSQL and SQLite, Turso and more. 

The lazygit of SQL databases. Connect to Postgres, MySQL, SQL Server, SQLite, Supabase, Turso, and more from your terminal in seconds.

Related contents:

- [sqlit - Quand y&amp;#039;en a marre de lancer SQL Server Management Studio pour une requête @ Korben :fr:](https://korben.info/sqlit-tui-sql-terminal-databases.html).]]>
            </summary>
            <updated>2025-12-22T08:34:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11185</id>
            <title type="text"><![CDATA[Feldera]]></title>
            <link rel="alternate" href="https://www.feldera.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11185"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The incremental computing engine for AI, ML and data teams.

 Feldera is a fast query engine for incremental computation. Feldera has the unique ability to evaluate arbitrary SQL programs incrementally, making it more powerful, expressive and performant than existing alternatives like batch engines, warehouses, stream processors or streaming databases. 

- [Feldera @ GitHub](https://github.com/feldera/feldera).

Related contents:

- [You Gotta Push If You Wanna Pull @ Gunnar Morling](https://www.morling.dev/blog/you-gotta-push-if-you-wanna-pull/).]]>
            </summary>
            <updated>2025-12-08T13:42:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11183</id>
            <title type="text"><![CDATA[data-peek]]></title>
            <link rel="alternate" href="https://www.datapeek.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11183"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fast PostgreSQL Client for Developers.

A minimal, fast SQL client desktop application with AI-powered querying. Built for developers who want to quickly peek at their data without the bloat. Supports PostgreSQL, MySQL, and Microsoft SQL Server.

- [data-peek @ GitHub](https://github.com/Rohithgilla12/data-peek).]]>
            </summary>
            <updated>2025-12-08T13:01:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10983</id>
            <title type="text"><![CDATA[RegreSQL]]></title>
            <link rel="alternate" href="https://github.com/boringSQL/regresql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10983"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Regression Testing your SQL queries.

The regresql tool implement a regression testing facility for SQL queries, and supports the PostgreSQL database system. A regression test allows to ensure known results when the code is edited.

Related contents:

- [RegreSQL: Regression Testing for PostgreSQL Queries @ boring SQL](https://boringsql.com/posts/regresql-testing-queries/).]]>
            </summary>
            <updated>2025-11-17T06:11:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10889</id>
            <title type="text"><![CDATA[Deepnote]]></title>
            <link rel="alternate" href="https://deepnote.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10889"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Analytics and data science notebook for teams. Jupyter notebook  for the AI era.

- Link Snowflake, BigQuery, CSVs, and 60+ data sources
- Write in Python, SQL, R — or just prompt Deepnote Agent
- Build powerful data apps and dashboards with AI

- [Deepnote @ GitHub](https://github.com/deepnote/deepnote).]]>
            </summary>
            <updated>2025-11-05T13:06:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10874</id>
            <title type="text"><![CDATA[xlsxsql]]></title>
            <link rel="alternate" href="https://github.com/noborus/xlsxsql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10874"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A CLI tool that executes SQL queries on xlsx files and outputs the results to various files, and also executes SQL queries on various files and outputs them to xlsx files.]]>
            </summary>
            <updated>2025-11-04T07:19:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10846</id>
            <title type="text"><![CDATA[Bruin]]></title>
            <link rel="alternate" href="https://getbruin.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10846"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your last data platform.
Reliable data. 10x faster, 90% less complexity.

 Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows. 

Bruin is a data pipeline tool that brings together data ingestion, data transformation with SQL &amp;amp; Python, and data quality into a single framework. It works with all the major data platforms and runs on your local machine, an EC2 instance, or GitHub Actions.

- [Bruin @ GitHub](https://github.com/bruin-data/bruin).

Related contents:

- [Digest #186: Inside the AWS Outage, Docker Compose in Production, F1 Hacks and 86,000 npm Packages Attacks @ DevOps Bulletin](https://www.devopsbulletin.com/p/digest-186-inside-the-aws-outage).]]>
            </summary>
            <updated>2025-11-03T10:19:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10808</id>
            <title type="text"><![CDATA[Apache Calcite]]></title>
            <link rel="alternate" href="https://calcite.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10808"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Dynamic data management framework.
The foundation for your next high-performance database.

It contains many of the pieces that comprise a typical database management system but omits the storage primitives. It provides an industry standard SQL parser and validator, a customisable optimizer with pluggable rules and cost functions, logical and physical algebraic operators, various transformation algorithms from SQL to algebra (and the opposite), and many adapters for executing SQL queries over Cassandra, Druid, Elasticsearch, MongoDB, Kafka, and others, with minimal configuration.

- [Apache Calcite @ GitHub](https://github.com/apache/calcite).

Related contents:

- [Reimagining log analytics for the modern enterprise @ OpenSearch](https://opensearch.org/blog/reimagining-log-analytics-for-the-modern-enterprise/).]]>
            </summary>
            <updated>2025-10-29T12:43:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10464</id>
            <title type="text"><![CDATA[SQLGlot]]></title>
            <link rel="alternate" href="https://sqlglot.com/sqlglot.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10464"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Python SQL Parser and Transpiler.

SQLGlot is a no-dependency SQL parser, transpiler, optimizer, and engine. It can be used to format SQL or translate between 31 different dialects like DuckDB, Presto / Trino, Spark / Databricks, Snowflake, and BigQuery. It aims to read a wide variety of SQL inputs and output syntactically and semantically correct SQL in the targeted dialects.

- [SQLGlot @ GitHub](https://github.com/tobymao/sqlglot).]]>
            </summary>
            <updated>2025-09-30T06:38:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10403</id>
            <title type="text"><![CDATA[Doctrine]]></title>
            <link rel="alternate" href="https://www.doctrine-project.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10403"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Doctrine Project is the home to several PHP libraries primarily focused on database storage and object mapping.

Related contents:

- [Domain specific language versus design patterns @  david duymelinck&amp;#039;s dev.to](https://dev.to/xwero/domain-specific-language-versus-design-patterns-23p4).
- [Your ORM Is Lying to You (And You&amp;#039;re Paying for It) @ HackerNoon](https://hackernoon.com/your-orm-is-lying-to-you-and-youre-paying-for-it).]]>
            </summary>
            <updated>2026-03-13T12:49:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10270</id>
            <title type="text"><![CDATA[SQLiteData]]></title>
            <link rel="alternate" href="https://github.com/pointfreeco/sqlite-data?utm_source=tldrwebdev" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10270"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A fast, lightweight replacement for SwiftData, powered by SQL and supporting CloudKit synchronization.]]>
            </summary>
            <updated>2025-09-18T11:37:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10252</id>
            <title type="text"><![CDATA[Malloy]]></title>
            <link rel="alternate" href="https://www.malloydata.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10252"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A modern open source language for analyzing,
transforming, and modeling data.

Malloy is a modern open source language for describing data relationships and transformations. It is both a semantic modeling language and a query language that uses an existing SQL engine to execute queries. Malloy currently can connect to BigQuery, Snowflake, PostgreSQL, MySQL, Trino, or Presto, and natively supports DuckDB. We&amp;#039;ve built a Visual Studio Code extension to facilitate building Malloy data models, querying and transforming data, and creating simple visualizations and dashboards.

- [Malloy @ GitHub](https://github.com/malloydata/malloy).

Related contents:

- [Lessons on building an AI data analyst @ Pedro Nascimento](https://www.pedronasc.com/articles/lessons-building-ai-data-analyst).]]>
            </summary>
            <updated>2025-09-17T14:29:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10211</id>
            <title type="text"><![CDATA[pgFormatter]]></title>
            <link rel="alternate" href="https://sqlformat.darold.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10211"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A PostgreSQL SQL syntax beautifier that can work as a console program or as a CGI. 

This SQL formatter/beautifier supports keywords from SQL-92, SQL-99, SQL-2003, SQL-2008, SQL-2011 and PostgreSQL specifics keywords. Works with any other databases too.

- [pgFormatter @ GitHub](https://github.com/darold/pgFormatter).]]>
            </summary>
            <updated>2025-09-15T13:34:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10081</id>
            <title type="text"><![CDATA[PostgreSQL MCP Server]]></title>
            <link rel="alternate" href="https://github.com/modelcontextprotocol/servers-archived/tree/main/src/postgres" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10081"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Model Context Protocol server that provides read-only access to PostgreSQL databases. This server enables LLMs to inspect database schemas and execute read-only queries.

Related contents:

- [MCP vulnerability case study: SQL injection in the Postgres MCP server @ Datadog](https://securitylabs.datadoghq.com/articles/mcp-vulnerability-case-study-SQL-injection-in-the-postgresql-mcp-server/).]]>
            </summary>
            <updated>2025-09-09T08:06:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/212</id>
            <title type="text"><![CDATA[Observable Framework]]></title>
            <link rel="alternate" href="https://observablehq.com/framework/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/212"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The best dashboards are built with code.
Create fast, beautiful data apps, dashboards, and reports from the command line. Write Markdown, JavaScript, SQL, Python, R… and any language you like. Free and open-source.

A static site generator for data apps, dashboards, reports, and more. Observable Framework combines JavaScript on the front-end for interactive graphics with any language on the back-end for data analysis. 

- [Observable Framework @ GitHub](https://github.com/observablehq/framework).]]>
            </summary>
            <updated>2025-10-21T14:50:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/214</id>
            <title type="text"><![CDATA[csvkit]]></title>
            <link rel="alternate" href="https://csvkit.readthedocs.io/en/latest/index.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/214"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[csvkit is a suite of command-line tools for converting to and working with CSV, the king of tabular file formats.

It is inspired by pdftk, GDAL and the original csvcut tool by Joe Germuska and Aaron Bycoffe.

It provides in2csv to convert xlsx to csv, and csvsql to populate a database with a csv file contents.

- [csvkit @ GitHub](https://github.com/wireservice/csvkit).]]>
            </summary>
            <updated>2025-10-21T14:50:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/466</id>
            <title type="text"><![CDATA[Sirius]]></title>
            <link rel="alternate" href="https://github.com/sirius-db/sirius" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/466"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Sirius is a GPU-native SQL engine. It plugs into existing databases such as DuckDB via the standard Substrait query format, requiring no query rewrites or major system changes. Sirius currently supports DuckDB and Doris (coming soon), other systems marked with * are on our roadmap.]]>
            </summary>
            <updated>2025-08-28T17:14:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/602</id>
            <title type="text"><![CDATA[SQLite-JS Extension]]></title>
            <link rel="alternate" href="https://github.com/sqliteai/sqlite-js" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/602"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Create custom SQLite functions in JavaScript. Extend your database with scalars, aggregates, window functions, and collations directly in JavaScript. 

SQLite-JS is a powerful extension that brings JavaScript capabilities to SQLite. With this extension, you can create custom SQLite functions, aggregates, window functions, and collation sequences using JavaScript code, allowing for flexible and powerful data manipulation directly within your SQLite database.]]>
            </summary>
            <updated>2025-08-28T17:38:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/643</id>
            <title type="text"><![CDATA[Lumosql]]></title>
            <link rel="alternate" href="https://lumosql.org/src/lumosql/doc/trunk/README.md" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/643"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[LumoSQL is a modification (not a fork) of the SQLite embedded data storage library, which is among the most-deployed software.
LumoSQL adds security, privacy, performance and measurement features to SQLite.]]>
            </summary>
            <updated>2025-08-28T17:46:13+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/661</id>
            <title type="text"><![CDATA[DuckLake]]></title>
            <link rel="alternate" href="https://ducklake.select/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/661"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[DuckLake is an integrated data lake and catalog format

DuckLake delivers advanced data lake features without traditional lakehouse complexity by using Parquet files and your SQL database. It&amp;#039;s an open, standalone format from the DuckDB team.

DuckLake is an open Lakehouse format that is built on SQL and Parquet. DuckLake stores metadata in a catalog database, and stores data in Parquet files. The DuckLake extension allows DuckDB to directly read and write data from DuckLake.

- [Ducklake @ GitHub](https://github.com/duckdb/ducklake).]]>
            </summary>
            <updated>2025-08-28T17:48:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/723</id>
            <title type="text"><![CDATA[Gmail to SQLite]]></title>
            <link rel="alternate" href="https://github.com/marcboeker/gmail-to-sqlite" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/723"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Index your Gmail account to a SQLite DB and play with the data. 

This is a script to download emails from Gmail and store them in a SQLite database for further analysis. I find it extremely useful to have all my emails in a database to run queries on them. For example, I can find out how many emails I received per sender, which emails take the most space, and which emails from which sender I never read.]]>
            </summary>
            <updated>2025-08-28T17:58:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/753</id>
            <title type="text"><![CDATA[Search Input Query]]></title>
            <link rel="alternate" href="https://github.com/williamcotton/search-input-query" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/753"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Search input query parser and React component.

A powerful search query language parser with SQL output support, inspired by Elasticsearch and Tantivy query syntax.]]>
            </summary>
            <updated>2025-08-28T18:03:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/754</id>
            <title type="text"><![CDATA[TextQuery]]></title>
            <link rel="alternate" href="https://textquery.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/754"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[All-in-One Desktop App to Analyze Data Locally.

TextQuery is an all-in-one desktop app to import, query, modify, and visualize your raw data with SQL.]]>
            </summary>
            <updated>2025-08-28T18:03:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/879</id>
            <title type="text"><![CDATA[DuckDB-DOOM]]></title>
            <link rel="alternate" href="https://github.com/patricktrainer/duckdb-doom" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/879"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Doom-like game using DuckDB.

A 3D first-person shooter game implemented entirely in SQL using DuckDB-WASM.

- [Abusing DuckDB-WASM by making SQL draw 3D graphics (Sort Of) @ 👋 🌎 Hey, Earth!](https://www.hey.earth/posts/duckdb-doom).]]>
            </summary>
            <updated>2025-08-28T18:24:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/918</id>
            <title type="text"><![CDATA[sqlc]]></title>
            <link rel="alternate" href="https://sqlc.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/918"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Compile SQL to type-safe code;
catch failures before they happen. 

- [sqlc @ GitHub](https://github.com/sqlc-dev/sqlc).]]>
            </summary>
            <updated>2025-08-28T18:30:43+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/955</id>
            <title type="text"><![CDATA[SQLite]]></title>
            <link rel="alternate" href="https://sqlite.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/955"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine. SQLite is the most used database engine in the world. SQLite is built into all mobile phones and most computers and comes bundled inside countless other applications that people use every day. More Information...

Related contents:

- [SQLite File Format Viewer](https://sqlite-internal.pages.dev/).
- [SQLite Transactions and Virtual Tables @ Misframe](https://misfra.me/2025/sqlite-transactions-and-virtual-tables/).
- [A faster way to copy SQLite databases between computers @, alexwlchan](https://alexwlchan.net/2025/copying-sqlite-databases/).
- [Scaling SQLite to 4M QPS on a single server (EC2 vs Bare Metal) @ Expensify](https://use.expensify.com/blog/scaling-sqlite-to-4m-qps-on-a-single-server).
- [PSA: SQLite WAL checksums fail silently and may lose data @ blag](https://avi.im/blag/2025/sqlite-wal-checksum/).
- [Lessons learned from building a sync-engine and reactivity system with SQLite @ Antoine&amp;#039;s blog](https://www.finkelstein.fr/sqlite-sync-engine-with-reactivity).
- [From 19k to 4.2M events/sec: story of a SQLite query optimisation @ mnt.io](https://mnt.io/articles/from-19k-to-4-2m-events-per-sec-story-of-a-sqlite-query-optimisation/).
- [SQLite Is ULTIMATE Choice For 99% of Projects @ DevOps Toolbox&amp;#039;s YouTube](https://www.youtube.com/watch?v=9RArbqGOvsw).
- [Subtleties of SQLite Indexes @ Evan Schwartz](https://emschwartz.me/subtleties-of-sqlite-indexes/).
- [SQLite concurrency and why you should care about it @ Jellyfin](https://jellyfin.org/posts/SQLite-locking/).
- [100000 TPS over a billion rows: the unreasonable effectiveness of SQLite @ anders murphy](https://andersmurphy.com/2025/12/02/100000-tps-over-a-billion-rows-the-unreasonable-effectiveness-of-sqlite.html).
- [The Silent Standard: Why the World’s Most Deployed Database Is Killing the Custom File Format @ WebProNews](https://www.webpronews.com/the-silent-standard-why-the-worlds-most-deployed-database-is-killing-the-custom-file-format/).
- [SQLite JSON Superpower: Virtual Columns + Indexing @ DB Pro](https://www.dbpro.app/blog/sqlite-json-virtual-columns-indexing).
- [I don&amp;#039;t buy SQLite in the cloud @ Monroe Clinton](https://monroeclinton.com/i-dont-buy-sqlite-in-the-cloud/).
- [SQLite 3.52 Released With WAL Corruption Fix and CLI Improvements @ linuxiac](https://linuxiac.com/sqlite-3-52-released-with-wal-corruption-fix-and-cli-improvements/).
- [Gotchas with SQLite in Production @ Anže&amp;#039;s Blog](https://blog.pecar.me/sqlite-prod/).
- [Modern SQLite: Features You Didn’t Know It Had @ slicker.me](https://slicker.me/sqlite/features.htm).
- [SQLite is All You Need for Durable Workflows @ Obelisk](https://obeli.sk/blog/sqlite-is-all-you-need-for-durable-workflows/).
- [SQLite improving performance with pre-sort @ anders murphy](https://andersmurphy.com/2026/06/07/sqlite-improving-performance-with-pre-sort.html).
- [Detecting Full Table Scans With SQLite @ Tenderlove Making](https://tenderlovemaking.com/2026/07/15/detecting-full-table-scans-with-sqlite/).
- [SQLite should have (Rust-style) editions @ Mort&amp;#039;s Ramblings](https://mort.coffee/home/sqlite-editions/).]]>
            </summary>
            <updated>2026-07-16T12:07:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1104</id>
            <title type="text"><![CDATA[Postgres Language Server]]></title>
            <link rel="alternate" href="https://pgtools.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1104"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A collection of language tools and a Language Server Protocol (LSP) implementation for Postgres, focusing on developer experience and reliable SQL tooling.

- [Postgres Language Server @ GitHub](https://github.com/supabase-community/postgres-language-server).
 
Related contents:

- [Postgres Language Server: Initial Release @ Supabase blog](https://supabase.com/blog/postgres-language-server).]]>
            </summary>
            <updated>2025-08-28T19:00:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1170</id>
            <title type="text"><![CDATA[pgledger]]></title>
            <link rel="alternate" href="https://github.com/pgr0ss/pgledger" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1170"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A ledger implementation in PostgreSQL.

Related contents:

- [Ledger Implementation in PostgreSQL @ Paul Gross&amp;#039;s Blog](https://www.pgrs.net/2025/03/24/pgledger-ledger-implementation-in-postgresql/).]]>
            </summary>
            <updated>2025-08-28T19:11:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1433</id>
            <title type="text"><![CDATA[Arroyo]]></title>
            <link rel="alternate" href="https://www.arroyo.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1433"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Cloud-native stream processing.  Distributed stream processing engine in Rust.

Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results.
Scale from zero to millions of events per second.

Arroyo is a distributed stream processing engine written in Rust, designed to efficiently perform stateful computations on streams of data. Unlike traditional batch processing, streaming engines can operate on both bounded and unbounded sources, emitting results as soon as they are available.

- [Arroyo @ GitHub](https://github.com/ArroyoSystems/arroyo).

Related contents:

- [Fast columnar JSON decoding with arrow-rs @ arroyo](https://www.arroyo.dev/blog/fast-arrow-json-decoding).]]>
            </summary>
            <updated>2025-08-28T19:55:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1466</id>
            <title type="text"><![CDATA[Directus]]></title>
            <link rel="alternate" href="https://directus.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1466"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Headless CMS + Backend for Every Custom Build.
Directus is a real-time API and App dashboard for managing SQL database content.
 The flexible backend for all your projects 🐰 Turn your DB into a headless CMS, admin panels, or apps with a custom UI, instant APIs, auth &amp;amp; more. 

Built for developers who need more than just a CMS. Manage complex content structures, handle digital assets, and control user permissions – all through an intuitive Studio.

- [Directus @ GitHub](https://github.com/directus/directus).

Related contents:

- [The last note taking app you&amp;#039;ll ever need @ Amber&amp;#039;s portfolio](https://amberwilliams.io/blogs/the-last-note-system).
- [Ditching Obsidian and building my own @ Amber&amp;#039;s portfolio](https://amberwilliams.io/blogs/building-my-own-pkms).
- [Is There a WordPress Replacement in 2026? I Went Looking @ Jean Galea](https://jeangalea.com/wordpress-replacement/).]]>
            </summary>
            <updated>2026-02-06T12:57:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1503</id>
            <title type="text"><![CDATA[StackQL]]></title>
            <link rel="alternate" href="https://stackql.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1503"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source, Multi Cloud, Analytics, IaC, more.
Provision. Query. Secure.

Query, provision and operate Cloud and SaaS resources and APIs using an extensible SQL based framework.
Deploy, manage and query cloud resources and interact with APIs using SQL.

- [StackQL @ GitHub](https://github.com/stackql/stackql).

Related content:

- [Introducing StackQL - Manage Your Cloud Services &amp;amp; Interact with APIs using SQL 🧑‍💻🔥 @ Madza&amp;#039;s dev.to](https://dev.to/madza/introducing-stackql-manage-your-cloud-services-interact-with-apis-using-sql-175m).]]>
            </summary>
            <updated>2025-08-28T20:07:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1540</id>
            <title type="text"><![CDATA[Use The Index, Luke]]></title>
            <link rel="alternate" href="https://use-the-index-luke.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1540"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQL Indexing and Tuning e-Book for developers.
Use The Index, Luke covers Oracle, MySQL, PostgreSQL, SQL Server, ...

A site explaining SQL indexing to developers—no crap about administration.
SQL indexing is the most effective tuning method—yet it is often neglected during development. Use The Index, Luke explains SQL indexing from grounds up and doesn’t stop at ORM tools like Hibernate.]]>
            </summary>
            <updated>2025-08-28T20:12:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1581</id>
            <title type="text"><![CDATA[SQL Noir]]></title>
            <link rel="alternate" href="https://www.sqlnoir.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1581"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A Detective SQL Game

SQL Noir is an interactive mystery-solving game where you crack cases by writing SQL queries.

- [SQL Noir @ GitHub](https://github.com/hristo2612/SQLNoir).]]>
            </summary>
            <updated>2025-08-28T20:19:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1736</id>
            <title type="text"><![CDATA[SQLMesh]]></title>
            <link rel="alternate" href="https://sqlmesh.readthedocs.io/en/stable/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1736"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Efficient data transformation and modeling framework that is backwards compatible with dbt.

SQLMesh is a next-generation data transformation framework designed to ship data quickly, efficiently, and without error. Data teams can efficiently run and deploy data transformations written in SQL or Python with visibility and control at any size.

- [SQLMesh @ GitHub](https://github.com/TobikoData/sqlmesh).

Related contents:

- [Why SQLMesh Might be The Best dbt Alternative @ The Data Toolbox](https://thedatatoolbox.substack.com/p/why-sqlmesh-might-be-the-best-dbt).]]>
            </summary>
            <updated>2025-08-28T20:45:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1820</id>
            <title type="text"><![CDATA[PostgreSQL execution plan visualizer]]></title>
            <link rel="alternate" href="https://explain.dalibo.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1820"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Visualizing and understanding PostgreSQL EXPLAIN plans made easy. 

A VueJS component to show a graphical vizualization of a PostgreSQL execution plan.

- [PostgreSQL execution plan visualizer 2 @ GitHub](https://github.com/dalibo/pev2).]]>
            </summary>
            <updated>2025-08-28T20:59:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1821</id>
            <title type="text"><![CDATA[pgMustard]]></title>
            <link rel="alternate" href="https://www.pgmustard.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1821"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[review Postgres query plans quickly.

A simple yet powerful tool to help you speed up queries. pgMustard speeds up your journey from knowing which query is a problem to working out what can be done about it.]]>
            </summary>
            <updated>2025-08-28T20:59:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1870</id>
            <title type="text"><![CDATA[Qustar]]></title>
            <link rel="alternate" href="https://github.com/tilyupo/qustar" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1870"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Query SQL database through an array-like API.]]>
            </summary>
            <updated>2025-08-28T21:08:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1962</id>
            <title type="text"><![CDATA[rqlite]]></title>
            <link rel="alternate" href="https://rqlite.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1962"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The lightweight, user-friendly, distributed relational database built on SQLite.
Fault tolerance and high availability with zero hassle.

- [rqlite @ GitHub](https://github.com/rqlite/rqlite).

Related contents:

- [How rqlite is tested @ Philip O&amp;#039;Toole ](https://philipotoole.com/how-is-rqlite-tested/).
- [The source code was the moat. But not anymore @ Philip O&amp;#039;Toole](https://philipotoole.com/the-source-code-was-the-moat-no-longer/).]]>
            </summary>
            <updated>2026-04-03T13:33:24+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2133</id>
            <title type="text"><![CDATA[osquery]]></title>
            <link rel="alternate" href="https://osquery.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2133"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Easily ask questions about your Linux, Windows, and macOS infrastructure.

- [osquery @ GitHub](https://github.com/osquery/osquery).

Related contents:

- [ 🔍OSQuery : L&amp;#039;outil Linux qui te parle en SQL ! 🚀 @ Laurent Biagiotti&amp;#039;s LinkedIn :fr:](https://www.linkedin.com/posts/laurent-biagiotti-19779284_%F0%9D%97%A2%F0%9D%97%A6%F0%9D%97%A4%F0%9D%98%82%F0%9D%97%B2%F0%9D%97%BF%F0%9D%98%86-loutil-linux-qui-te-parle-activity-7282282342855897088-t-jc/).]]>
            </summary>
            <updated>2025-08-28T21:52:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2212</id>
            <title type="text"><![CDATA[Musoq]]></title>
            <link rel="alternate" href="https://puchaczov.github.io/Musoq/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2212"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQL-like Querying for Various Data Sources.

Musoq lets you use SQL-like queries on files, directories, images and other data sources without a database. It&amp;#039;s designed to ease life for developers.

Musoq is a tool that lets developers and IT professionals query different data sources using SQL-like syntax, without needing to import data into a database first. It’s designed for scenarios where you need to analyze files, directories, archives, or other data sources quickly and efficiently.

- [Musoq @ GitHub](https://github.com/Puchaczov/Musoq).]]>
            </summary>
            <updated>2025-08-28T22:04:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2222</id>
            <title type="text"><![CDATA[SDF Labs]]></title>
            <link rel="alternate" href="https://www.sdf.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2222"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Data Runs Better on SDF. Transform Data Better with SDF.
SDF is the fastest way to build a scalable, reliable, and optimized data warehouse.

SDF is a developer platform for data that scales SQL understanding across an organization, empowering all data teams to unlock the full potential of their data.

SDF is a multi-dialect SQL compiler, transformation framework, and analytical database engine. It natively compiles SQL dialects, like Snowflake, and connects to their corresponding data warehouses to materialize models.

- [SDF Docs](https://docs.sdf.com/).
- [SDF @ GitHub](https://github.com/sdf-labs/sdf-cli).

Source: [Testing is Not Enough: Transforming Data Quality with Write, Audit, Publish using SDF Build @ SDF Blog](https://blog.sdf.com/p/testing-is-not-enough-transforming).]]>
            </summary>
            <updated>2025-08-28T22:06:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2314</id>
            <title type="text"><![CDATA[myexplainer]]></title>
            <link rel="alternate" href="https://github.com/mmartinjoo/myexplainer" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2314"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[✨A CLI tool for analyzing queries and DB tables for MySQL.]]>
            </summary>
            <updated>2025-08-28T22:21:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2323</id>
            <title type="text"><![CDATA[SQLAlchemy]]></title>
            <link rel="alternate" href="https://www.sqlalchemy.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2323"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Database Toolkit for Python.

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.

It provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language.

- [SQLAlchemy @ GitHub](https://github.com/sqlalchemy/sqlalchemy).
- [SqlAlchemy, l&amp;#039;ORM Python - Partie 1 @ DevSecOps :fr:](https://blog.stephane-robert.info/docs/developper/programmation/python/sqlachemy-1/).]]>
            </summary>
            <updated>2025-08-28T22:24:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2347</id>
            <title type="text"><![CDATA[Amazon Aurora DSQL]]></title>
            <link rel="alternate" href="https://aws.amazon.com/fr/rds/aurora/dsql/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2347"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Distributed SQL Databases

Fastest serverless distributed SQL database for always available applications.

- [AWS announces Aurora DSQL, a new distributed SQL database that promises virtually unlimited scalability @ TechCrunch](https://techcrunch.com/2024/12/03/aws-announces-aurora-dsql-a-new-distributed-sql-database-that-promises-virtually-unlimited-scalability/).]]>
            </summary>
            <updated>2025-08-28T22:28:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2408</id>
            <title type="text"><![CDATA[sqls]]></title>
            <link rel="alternate" href="https://github.com/sqls-server/sqls" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2408"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQL language server written in Go.

sqls aims to provide advanced intelligence for you to edit sql in your own editor.]]>
            </summary>
            <updated>2025-10-28T07:09:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2490</id>
            <title type="text"><![CDATA[Wren AI]]></title>
            <link rel="alternate" href="https://getwren.ai/oss" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2490"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source sQL AI Agent. Text2SQL made Easy!

Wren AI is an open-source SQL AI Agent that empowers data, product, and business teams to access insights through AI chat, built-in well designed intuitive UI and UX, integrating seamlessly with tools like Excel and Google Sheets.

- [Wren AI @ GitHub](https://github.com/Canner/WrenAI).]]>
            </summary>
            <updated>2025-08-28T22:50:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2559</id>
            <title type="text"><![CDATA[SQL Police Department]]></title>
            <link rel="alternate" href="https://sqlpd.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2559"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Learn SQL while solving crimes!]]>
            </summary>
            <updated>2025-08-28T23:03:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2580</id>
            <title type="text"><![CDATA[rust-query]]></title>
            <link rel="alternate" href="https://github.com/LHolten/rust-query" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2580"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Type safe queries using the Rust type system.

The goal of this library is to allow writing relational database queries using familiar Rust syntax. The library should guarantee that a query can not fail if it compiles. This already includes preventing use after free for row ids passed between queries and even database migrations!]]>
            </summary>
            <updated>2025-08-28T23:06:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2593</id>
            <title type="text"><![CDATA[Apache Iceberg™]]></title>
            <link rel="alternate" href="https://iceberg.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2593"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The open table format for analytic datasets.

Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time.

- [Apache Iceberg @ GitHub](https://github.com/apache/iceberg).

Related contents:

- [PyIceberg: Current State and Roadmap @ Ju Data Engineering Newsletter](https://juhache.substack.com/p/pyiceberg-current-state-and-roadmap).
- [The Equality Delete Problem in Apache Iceberg @ Data Engineer Things&amp;#039;s Medium](https://blog.dataengineerthings.org/the-equality-delete-problem-in-apache-iceberg-143dd451a974).
- [How I Saved Millions by Restructuring Iceberg Metadata @ Gautham Gondi&amp;#039;s Medium](https://medium.com/@gauthamnagendra/how-i-saved-millions-by-restructuring-iceberg-metadata-c4f5c1de69c2).
- [High Throughput Ingestion with Iceberg @ Adobe Tech Blog&amp;#039;s Medium](https://medium.com/adobetech/high-throughput-ingestion-with-iceberg-ccf7877a413f).
- [Scaling Iceberg Writes with Confidence: A Conflict-Free Distributed Architecture for Fast, Concurrent, Consistent Append-Only Writes @ e6data](https://www.e6data.com/blog/iceberg-distributed-architecture-fast-concurrent-append-writes).
- [Postgres Is the Gateway Drug @ Vignesh Ravichandran](https://viggy28.dev/article/postgres-gateway-drug/).]]>
            </summary>
            <updated>2026-03-23T16:38:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2615</id>
            <title type="text"><![CDATA[PostgreSQL]]></title>
            <link rel="alternate" href="https://www.postgresql.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2615"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The world&amp;#039;s most advanced open source database.

Related contents:

- [You Just Need Postgres](https://youjustneedpostgres.com/).
- [Postgres Locks Explained](https://postgreslocksexplained.com/).
- [What I Wish Someone Told Me About Postgres @ ChallahScript](https://challahscript.com/what_i_wish_someone_told_me_about_postgres#jsonb-is-a-sharp-knife).
- [Logical replication in Postgres: Basics @ EDB](https://www.enterprisedb.com/blog/logical-replication-postgres-basics).
- [Database sharding case study: PostgreSQL @ The Polymathic Engineer](https://newsletter.francofernando.com/p/database-sharding-case-study-postgresql).
- [I Tried Every Open Source Database and Found Only One That is Actually Useful @ Hacker Noon](https://hackernoon.com/i-tried-every-open-source-database-and-found-only-one-that-is-actually-useful).
- [How direct TLS can speed up your connections @ Marc Bowes](https://marc-bowes.com/postgres-direct-tls.html).
- [PostgreSQL pour remplacer Redis @ Rodolphe Bréard
 :fr:](https://rodolphe.breard.tf/article/postgresql-pour-remplacer-redis/).
- [One more reason to choose Postgres over MySQL @ tanin](https://tanin.nanakorn.com/one-more-reason-to-use-postgres-vs-mysql/).
- [From 99.9% to 99.99%: Building PostgreSQL Resilience into Your Product Architecture @ Stormatics](https://stormatics.tech/blogs/building-postgresql-resilience-into-your-product-architecture).
- [Handling unique indexes on large data in PostgreSQL @ Volodymyr Potiichuk](https://volodymyrpotiichuk.com/blog/articles/unique-indexes-on-large-data-in-postgres-sql).
- [Postgres Internals Deep Dive: Process Architecture @ EDB Postgres](https://www.enterprisedb.com/blog/postgres-internals-deep-dive-process-architecture).
- [PostgreSQL maintenance without superuser @ boringSQL](https://boringsql.com/posts/postgresql-predefined-roles/).
- [Postgres’ Original Project Goals: The Creators Totally Nailed It @ Chunchy Data](https://www.crunchydata.com/blog/the-postgres-project-original-goals-and-how-the-creators-totally-nailed-it).
- [Redis is fast - I&amp;#039;ll cache in Postgres @ Dizzy zone](https://dizzy.zone/2025/09/24/Redis-is-fast-Ill-cache-in-Postgres/).
- [PostgreSQL MVCC Explained (Simply!) @ SauravDhakal&amp;#039;s Substack](https://substack.com/home/post/p-171617759).
- [Postgres Partitioning Best Practices: Sofia&amp;#039;s Story @ Karen Jex](https://karenjex.blogspot.com/2025/09/postgres-partitioning-best-practices.html).
- [Tuning AIO in PostgreSQL 18 @ Tomas Vondra](https://vondra.me/posts/tuning-aio-in-postgresql-18/).
- [Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization @ Frontend Masters](https://frontendmasters.com/blog/advanced-postgresql-indexing/).
- [The best worst hack that saved our bacon @ Jefferson Heard](https://jeffersonheard.ghost.io/the-best-worst-hack-that-saved-our-bacon/).
- [Going down the rabbit hole of Postgres 18 features @ xata](https://xata.io/blog/going-down-the-rabbit-hole-of-postgres-18-features).
- [JIT: so you want to be faster than an interpreter on modern CPUs… @ Pinaraf&amp;#039;s website](https://www.pinaraf.info/2025/10/jit-so-you-want-to-be-faster-than-an-interpreter-on-modern-cpus/).
- [Postgres 18: OLD and NEW Rows in the RETURNING Clause @ crunchy data](https://www.crunchydata.com/blog/postgres-18-old-and-new-in-the-returning-clause).
- [Benchmarking Postgres 17 vs 18 @ PlanetScale](https://planetscale.com/blog/benchmarking-postgres-17-vs-18).
- [Is Postgres Read Heavy or Write Heavy? (And Why You Should You Care) @ crunchy data](https://www.crunchydata.com/blog/is-postgres-read-heavy-or-write-heavy-and-why-should-you-care).
- [Pipelining in psql (PostgreSQL 18) @ PostgreSQL Notes - Daniel Vérité](https://postgresql.verite.pro/blog/2025/10/01/psql-pipeline.html).
- [Kafka is fast -- I&amp;#039;ll use Postgres @ TopicPartition](https://topicpartition.io/blog/postgres-pubsub-queue-benchmarks).
- [Redis is fast - I&amp;#039;ll cache in Postgres @ Dizzy zone](https://dizzy.zone/2025/09/24/Redis-is-fast-Ill-cache-in-Postgres/).
- [Moving tables across PostgreSQL instances @ Anantha Kumaran](https://ananthakumaran.in/2025/11/02/moving-tables-across-postgres-instances.html).
- [Absurd Workflows: Durable Execution With Just Postgres @ Armin Ronacher&amp;#039;s Thoughts and Writings](https://lucumr.pocoo.org/2025/11/3/absurd-workflows/).
- [Don&amp;#039;t give Postgres too much memory @ Tomas Vondra](https://vondra.me/posts/dont-give-postgres-too-much-memory/).
- [Moving tables across PostgreSQL instances @ Anantha Kumaran](https://ananthakumaran.in/2025/11/02/moving-tables-across-postgres-instances.html).
- [Postgres Internals Hiding in Plain Sight @ crunchy data](https://www.crunchydata.com/blog/postgres-internals-hiding-in-plain-sight).
- [#PostgresMarathon 2-013: Why keep your index set lean @ PostgresAI](https://postgres.ai/blog/20251110-postgres-marathon-2-013-why-keep-your-index-set-lean).
- [99% of Developers Don&amp;#039;t Get PostgreSQL @ The Coding Gopher&amp;#039;s YouTube](https://www .youtube.com/watch?v=P8rrhZTPEAQ).
- [PostgreSQL DBA @ Developer Roadmaps](https://roadmap.sh/postgresql-dba).
- [How/Why to Sweep Async Tasks Under a Postgres Table @ taylor.town](https://taylor.town/pg-task).
- [Instant database clones with PostgreSQL 18 @ boringSQL](https://boringsql.com/posts/instant-database-clones/).
- [Go ahead, self-host Postgres @ Pierce Freeman](https://pierce.dev/notes/go-ahead-self-host-postgres).
- [PostgreSQL 18 RETURNING Enhancements: A Game Changer for Modern Applications @ pgEdge](https://www.pgedge.com/blog/postgresql-18-returning-enhancements-a-game-changer-for-modern-applications).
- [The hidden cost of PostgreSQL arrays @ boringSQL](https://boringsql.com/posts/good-bad-arrays/).
- [Life Altering Postgresql Patterns @ mccue.dev](https://mccue.dev/pages/3-11-25-life-altering-postgresql-patterns).
- [Unconventional PostgreSQL Optimizations @ Haki Benita](https://hakibenita.com/postgresql-unconventional-optimizations).
- [I Replaced Redis with PostgreSQL (And It&amp;#039;s Faster) @ Polliog&amp;#039;s dev.to](https://dev.to/polliog/i-replaced-redis-with-postgresql-and-its-faster-4942).
- [Using PostgreSQL as a Dead Letter Queue for Event-Driven Systems @ Diljit&amp;#039;s Corner](https://www.diljitpr.net/blog-post-postgresql-dlq).
- [Introduction to PostgreSQL Indexes @ Dalto Curvelano](https://dlt.github.io/blog/posts/introduction-to-postgresql-indexes/).
- [Introducing: Postgres Best Practices @ supabase](https://supabase.com/blog/postgres-best-practices-for-ai-agents).
- [Postgres Postmaster does not scale @ recall.ai](https://www.recall.ai/blog/postgres-postmaster-does-not-scale).
- [Futureproofing Tines: Partitioning a 17TB table in PostgreSQL @ tines](https://www.tines.com/blog/futureproofing-tines-partitioning-a-17tb-table-in-postgresql/).
- [Database Indexing @ AkashSDas&amp;#039; Medium](https://medium.com/@akashsdas_dev/database-indexing-e10362624ed3).
- [Scaling PostgreSQL to power 800 million ChatGPT users @ OpenAI](https://openai.com/index/scaling-postgresql/).
- [Unlocking High-Performance PostgreSQL: Key Memory Optimizations @ Stormatics](https://stormatics.tech/blogs/unlocking-high-performance-postgresql-key-memory-optimizations).
- [Six Signs That Postgres Tuning Won&amp;#039;t Fix Your Performance Problems @ TigerData](https://www.tigerdata.com/blog/six-signs-postgres-tuning-wont-fix-performance-problems).
- [PostgreSQL Bloat Is a Feature, Not a Bug @ Roger Welin](https://rogerwelin.github.io/2026/02/11/postgresql-bloat-is-a-feature-not-a-bug/).
- [Read efficiency issues in Postgres queries @ pg mustard](https://www.pgmustard.com/blog/read-efficiency-issues-in-postgres-queries).
- [The real cost of random I/O @ Tomas Vondra](https://vondra.me/posts/the-real-cost-of-random-io/).
- [Production query plans without production data @ Boring SQL](https://boringsql.com/posts/portable-stats/).
- [Rust is slowly but surely eating PostgreSQL: Deep dive into Neon, ParadeDB, PgDog and more @ Sylvain Kerkour](https://kerkour.com/rust-eating-postgres).
- [How We Optimized Top K in Postgres @ ParadeDB](https://www.paradedb.com/blog/optimizing-top-k).
- [Using Rust and Postgres for everything: patterns learned over the years @ Sylvain Kerkour](https://kerkour.com/rust-postgres-everything).
- [Ctrl-C in psql gives me the heebie-jeebies @ Neon](https://neon.com/blog/ctrl-c-in-psql-gives-me-the-heebie-jeebies).
- [When upserts don&amp;#039;t update but still write: Debugging Postgres performance at scale @ Datadog](https://www.datadoghq.com/blog/engineering/debugging-postgres-performance/).
- [Introduction to PostgreSQL Indexes @ explain, analyze](https://dlt.github.io/blog/posts/introduction-to-postgresql-indexes/).
- [Keeping a Postgres queue healthy @ PlanetScale](https://planetscale.com/blog/keeping-a-postgres-queue-healthy).
- [I replaced my entire stack with Postgres... @ The Coding Gopher](https://www.youtube.com/watch?v=TdondBmyNXc).
-  [Does Postgres Scale? @ DBOS](https://www.dbos.dev/blog/benchmarking-workflow-execution-scalability-on-postgres).
- [The &amp;quot;Just Use Postgres&amp;quot; Trap @ CodeOpinion&amp;#039;s YouTube](https://www.youtube.com/watch?v=ACVevIlWEfM).
- [How we saved ~40GB of Postgres space wasted on indexes @ Ravi Ojha&amp;#039;s peer list](https://peerlist.io/raviojhax/articles/how-unused-indexes-ate-41gb-postgres).
- [Vos requêtes SQL jusqu&amp;#039;à 10000 fois plus rapides, durablement. - Alain LESAGE (DALIBO) @ Devoxx France&amp;#039;s YouTube :fr:](https://www.youtube.com/watch?v=TAJKNBPv4Wc).
- [Handling graphs with SQL/PGQ in PostgreSQL @ Cybertec](https://www.cybertec-postgresql.com/en/handling-graphs-with-sql-pgq-in-postgresql/).
- [When failover isn’t safe: Building high-availability PostgreSQL on Kubernetes @ Datadog Engineering](https://www.datadoghq.com/blog/engineering/postgresql-ha-kubernetes/).
- [The only scalable delete in Postgres is DROP TABLE @ Planetscale](https://planetscale.com/blog/the-only-scalable-delete).
- [The NULL in your NOT IN @ boringSQL](https://boringsql.com/posts/not-in-null/).
- [The feedback loops behind Kubernetes @ Planetscale](https://planetscale.com/blog/the-feedback-loops-behind-kubernetes).
- [Too many tables are bad for you @ Cybertec](https://www.cybertec-postgresql.com/en/too-many-tables-are-bad/).
- [PostgreSQL and the OOM Killer: Why We Use Strict Memory Overcommit @ ubicloud](https://www.ubicloud.com/blog/postgresql-and-the-oom-killer-why-we-use-strict-memory-overcommit).
- [How to Achieve Pruning When Querying by Non-Partitioned Columns in PostgreSQL @ Haki Benita](https://hakibenita.com/postgresql-partition-pruning).
- [The four horsemen behind thousands of Postgres outages @ malisper.me](https://malisper.me/the-four-horsemen-behind-thousands-of-postgres-outages/).
- [PostgreSQL as a temporal database @ xata](https://xata.io/blog/postgres-as-a-temporal-db).
- [Repeatable Read vs Snapshot Isolation @ jaymcor.github.io](https://jaymcor.github.io/notes/isolation_rr_si.html).]]>
            </summary>
            <updated>2026-07-20T12:06:45+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2655</id>
            <title type="text"><![CDATA[litdb]]></title>
            <link rel="alternate" href="https://litdb.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2655"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[type safe SQL for TypeScript/JavaScript.
Lightweight RDBMS agnostic TypeScript/JS abstraction for SQLite, PostgreSQL and MySQL.

SQL you know but type safe parameterized, expressive &amp;amp; portable.

litdb contains LINQ-like type-safe SQL builders for TypeScript/JavaScript for writing type-safe expressive SQL that&amp;#039;s parameterized &amp;amp; portable across SQLite, MySQL &amp;amp; PostgreSQL.

-  [litdb @ GitHub](https://github.com/litdb/litdb).]]>
            </summary>
            <updated>2025-08-28T23:19:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2847</id>
            <title type="text"><![CDATA[React Query Builder]]></title>
            <link rel="alternate" href="https://react-querybuilder.js.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2847"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Query Builder Component for React.

React Query Builder is a fully customizable query builder component for React, along with a collection of utility functions for importing from, and exporting to, various query languages like SQL, MongoDB, and more.

- [React Query Builder @ GitHub](https://github.com/react-querybuilder/react-querybuilder).]]>
            </summary>
            <updated>2025-08-28T23:51:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2850</id>
            <title type="text"><![CDATA[SQL style guide]]></title>
            <link rel="alternate" href="https://www.sqlstyle.guide/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2850"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A consistent code style guide for SQL to ensure legible and maintainable projects.

- [SQL style guide @ GitHub](https://github.com/treffynnon/sqlstyle.guide).]]>
            </summary>
            <updated>2025-08-28T23:51:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2897</id>
            <title type="text"><![CDATA[SQLMap Command Generator]]></title>
            <link rel="alternate" href="https://acorzo1983.github.io/SQLMapCG/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2897"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A web-based tool to easily generate customizable SQLMap commands for testing SQL injection vulnerabilities. Features include target configuration, connection options, detection levels, and various SQL injection techniques. Perfect for penetration testers and security enthusiasts. 

- [SQLMap Command Generator @ GitHub](https://github.com/acorzo1983/SQLMapCG/).]]>
            </summary>
            <updated>2025-08-28T23:59:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2940</id>
            <title type="text"><![CDATA[Evidence]]></title>
            <link rel="alternate" href="https://evidence.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2940"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Business Intelligence as Code. Build polished data products with SQL.
Build fast, interactive data visualizations in pure SQL and markdown.

Evidence is a lightweight framework for building data apps. It&amp;#039;s open source and free to get started.

- [Evidence @ GitHub](https://github.com/evidence-dev/evidence).]]>
            </summary>
            <updated>2025-08-29T00:07:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2996</id>
            <title type="text"><![CDATA[CSV SQL Tool]]></title>
            <link rel="alternate" href="https://csvsqltool.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2996"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Run SQL queries on CSV files directly in your browser. No data leaves your browser.
Fast, private, and easy to use.]]>
            </summary>
            <updated>2025-08-29T00:16:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3025</id>
            <title type="text"><![CDATA[SQL tips and tricks]]></title>
            <link rel="alternate" href="https://github.com/ben-n93/SQL-tips-and-tricks" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3025"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A (somewhat opinionated) list of SQL tips and tricks that I&amp;#039;ve picked up over the years.

There&amp;#039;s so much you can you do with SQL but I&amp;#039;ve focused on what I find most useful in my day-to-day work as a data analyst and what I wish I had known when I first started writing SQL.

- [OpenLampTech No. 154](https://openlamptech.substack.com/p/openlamptech-no-154).]]>
            </summary>
            <updated>2025-08-29T00:20:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3100</id>
            <title type="text"><![CDATA[Anyquery]]></title>
            <link rel="alternate" href="https://anyquery.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3100"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Use SQL for everything. Query anything with old-school cool SQL.

Anyquery is a CLI tool to run SQL queries on any data source, no matter if it&amp;#039;s a file, an API, logs, or a local app.
See the integrations for the full extent of what you can do. 

- [Anyquery @ GitHub](https://github.com/julien040/anyquery).]]>
            </summary>
            <updated>2025-08-29T00:33:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3117</id>
            <title type="text"><![CDATA[Vanna.AI]]></title>
            <link rel="alternate" href="https://vanna.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3117"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄. 

Personalized AI SQL Agent. Let Vanna.AI write your SQL for you

The fastest way to get actionable insights from your database just by asking questions.

- [Vanna @ GitHub](https://github.com/vanna-ai/vanna).]]>
            </summary>
            <updated>2025-08-29T00:36:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3323</id>
            <title type="text"><![CDATA[sq]]></title>
            <link rel="alternate" href="https://sq.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3323"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[wrangle data.

sq is a command line tool that provides jq-style access to structured data sources: SQL databases, or document formats like CSV or Excel. It is the lovechild of sql+jq.

- [sq @ GitHub](https://github.com/neilotoole/sq).]]>
            </summary>
            <updated>2025-08-29T01:10:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3396</id>
            <title type="text"><![CDATA[Proof of SQL]]></title>
            <link rel="alternate" href="https://github.com/spaceandtimelabs/sxt-proof-of-sql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3396"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Proof of SQL is a high performance zero knowledge (ZK) prover developed by the Space and Time team, which cryptographically guarantees SQL queries were computed accurately against untampered data. It targets online latencies while proving computations over entire chain histories, an order of magnitude faster than state-of-the art zkVMs and coprocessors.]]>
            </summary>
            <updated>2025-08-29T01:22:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3399</id>
            <title type="text"><![CDATA[Materialize]]></title>
            <link rel="alternate" href="https://materialize.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3399"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Cloud Operational Data Store. Use SQL to transform, deliver, and act on fast-changing data.

Materialize is a cloud-native data warehouse purpose-built for operational workloads where an analytical data warehouse would be too slow, and a stream processor would be too complicated.

Using SQL and common tools in the wider data ecosystem, Materialize allows you to build real-time automation, engaging customer experiences, and interactive data products that drive value for your business while reducing the cost of data freshness.

- [Materialize @ GitHub](https://github.com/MaterializeInc/materialize).]]>
            </summary>
            <updated>2025-08-29T01:22:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3446</id>
            <title type="text"><![CDATA[FerretDB]]></title>
            <link rel="alternate" href="https://www.ferretdb.com/?ref=selfh.st" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3446"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[FerretDB allows you to use MongoDB drivers seamlessly with PostgreSQL as the database backend. Use all tools, drivers, UIs, and the same query language and stay open-source. 

- [FerretDB @ GitHub](https://github.com/FerretDB/FerretDB).]]>
            </summary>
            <updated>2025-08-29T01:31:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3473</id>
            <title type="text"><![CDATA[meilibridge]]></title>
            <link rel="alternate" href="https://github.com/ja7ad/meilibridge" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3473"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[meilibridge is a robust package designed to seamlessly sync data from both SQL and NoSQL databases to Meilisearch, providing an efficient and unified search solution. 

- [Veille de la semaine du 5 août 2024 @ Veille de la semaine&amp;#039;s Substack :fr:](https://guikingone.substack.com/p/veille-de-la-semaine-du-5-aout-2024)]]>
            </summary>
            <updated>2025-08-29T01:35:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3654</id>
            <title type="text"><![CDATA[The Querynomicon]]></title>
            <link rel="alternate" href="https://gvwilson.github.io/sql-tutorial/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3654"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Upon first encountering SQL after two decades of Fortran, C, Java, and Python, I thought I had stumbled into hell. I quickly realized that was optimistic: after all, hell has rules.

I have since realized that SQL does too, and that they are no more confusing or contradictory than those of most other programming languages. They only appear so because it draws on a tradition unfamiliar to those of us raised with derivatives of C. To quote Terry Pratchett, it is not mad, just differently sane.

Welcome, then, to a world in which the strange will become familiar, and the familiar, strange. Welcome, thrice welcome, to SQL.

- [The Querynomicon: An Introduction to SQL for Weary Data Scientists @ GitHub](https://github.com/gvwilson/sql-tutorial).]]>
            </summary>
            <updated>2025-08-29T02:05:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4018</id>
            <title type="text"><![CDATA[Apache DataFusion]]></title>
            <link rel="alternate" href="https://datafusion.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4018"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[DataFusion is a very fast, extensible query engine for building high-quality data-centric systems in Rust, using the Apache Arrow in-memory format.

DataFusion is great for building projects such as domain specific query engines, new database platforms and data pipelines, query languages and more. It lets you start quickly from a fully working engine, and then customize those features specific to your use.

- [DataFusion @ GitHub](https://github.com/apache/datafusion).]]>
            </summary>
            <updated>2025-08-29T03:06:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4020</id>
            <title type="text"><![CDATA[GraphJin]]></title>
            <link rel="alternate" href="https://graphjin.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4020"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Build APIs in 5 minutes. Build NodeJS / GO APIs in 5 minutes not weeks.
A GraphQL-to-SQL converting app.

Just write simple GraphQL queries to define the data you need and GraphJin will auto-magically convert them into efficient SQL queries and fetch the data you need.

- [GraphJin @ GitHub](https://github.com/dosco/graphjin).
- [Comparing plain SQL, ORM and GraphQL performance in Golang @ Mastodon](https://www.amazingcto.com/graphql-for-server-development/).
- [Just Use Postgres for Everything @ Amazing CTO](https://www.amazingcto.com/postgres-for-everything/).]]>
            </summary>
            <updated>2025-08-29T03:06:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4051</id>
            <title type="text"><![CDATA[Cube]]></title>
            <link rel="alternate" href="https://cube.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4051"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[📊 Cube — The Semantic Layer for Building Data Applications.
The Universal Semantic Layer.

Build trust with a semantic layer. Connect siloed data, define consistent metrics, and power AI and analytics with context.

Cube is the semantic layer for building data applications. It helps data engineers and application developers access data from modern data stores, organize it into consistent definitions, and deliver it to every application.

Cube was designed to work with all SQL-enabled data sources, including cloud data warehouses like Snowflake or Google BigQuery, query engines like Presto or Amazon Athena, and application databases like Postgres. Cube has a built-in relational caching engine to provide sub-second latency and high concurrency for API requests.

- [Cube @ GitHub](https://github.com/cube-js/cube).
- [\#264.exe - GraphQL: Votre nouveau BFF par Christophe Blefari @ &amp;lt;ifttd&amp;gt;](https://www.ifttd.io/episodes/graphql#w-tabs-0-data-w-pane-3).
- [le semantic layer va vous plaire @ Florent J.&amp;#039;s LinkedIn :fr:](https://www.linkedin.com/posts/florent-j-93716410b_vous-voulez-que-nimporte-qui-dans-activity-7152555059996729345-Xh5X/).]]>
            </summary>
            <updated>2025-08-29T03:11:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4053</id>
            <title type="text"><![CDATA[YDB]]></title>
            <link rel="alternate" href="https://ydb.tech/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4053"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[an open source Distributed SQL Database.

YDB is a versatile open source Distributed SQL Database that combines high availability and scalability with strong consistency and ACID transactions. It accommodates transactional (OLTP), analytical (OLAP), and streaming workloads simultaneously.

- [YDB @ GitHub](https://github.com/ydb-platform/ydb).]]>
            </summary>
            <updated>2025-08-29T03:11:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4125</id>
            <title type="text"><![CDATA[AdminerEvo]]></title>
            <link rel="alternate" href="https://docs.adminerevo.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4125"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AdminerEvo is a web-based database management interface, with a focus on security, user experience, performance, functionality and size. 

AdminerEvo works out of the box with MySQL, MariaDB, PostgreSQL, SQLite, MS SQL, Oracle, Elasticsearch and MongoDB. In addition, there are plugins for SimpleDB, Firebird and ClickHouse.

- [AdminerEvo @ GitHub](https://github.com/adminerevo/adminerevo).]]>
            </summary>
            <updated>2025-08-29T03:24:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4126</id>
            <title type="text"><![CDATA[DbGate]]></title>
            <link rel="alternate" href="https://dbgate.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4126"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source SQL+noSQL Database Client. The Smartest SQL+noSQL Database Client.

Database manager for MySQL, PostgreSQL, SQL Server, MongoDB, SQLite and others. Runs under Windows, Linux, Mac or as web application 

- [DbGate Community](https://dbgate.org/).
- [DbGate @ GitHub](https://github.com/dbgate/dbgate).]]>
            </summary>
            <updated>2025-09-08T09:15:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4164</id>
            <title type="text"><![CDATA[BigTesty]]></title>
            <link rel="alternate" href="https://tosun-si.github.io/bigtesty/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4164"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[BigTesty: integration testing for BigQuery.

BigTesty is a framework that allows to create Integration Tests with BigQuery on a real and short-lived Infrastructure.
Integration and End-to-End tests are a robust way to validate if SQL queries work as expected.
There is no an emulator in this case and the queries are executed directly in the BigQuery Engine.

- [BigTesty @ GitHub](https://github.com/tosun-si/bigtesty).
- [BigTesty: Integration Testing library for BigQuery @ GCP Learning with Mazlum &amp;amp; GroupBees&amp;#039; YouTube](https://www.youtube.com/watch?v=qKup69FOo0s).]]>
            </summary>
            <updated>2025-08-29T03:31:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4214</id>
            <title type="text"><![CDATA[Dataherald AI]]></title>
            <link rel="alternate" href="https://dataherald.readthedocs.io/en/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4214"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Dataherald is a natural language-to-SQL engine built for enterprise-level question answering over relational data. It allows you to set up an API from your database that can answer questions in plain English.]]>
            </summary>
            <updated>2025-08-29T03:39:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4323</id>
            <title type="text"><![CDATA[dbt]]></title>
            <link rel="alternate" href="https://www.getdbt.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4323"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Transform Data in Your Warehouse. Build trusted data products faster.

Accelerate your data transformation process with dbt Cloud and start delivering data that you and your team can rely on.  dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. Analysts using dbt can transform their data by simply writing select statements, while dbt handles turning these statements into tables and views in a data warehouse.

- [dbt Core @ GitHub](https://github.com/dbt-labs/dbt-core).
- [dbt Developer Hub](https://docs.getdbt.com/).

Sources:

- [268 - Résilience de la data - Sammy Teillet @ &amp;lt;ifttd&amp;gt; :fr:](https://www.ifttd.io/episodes/resilience-de-la-data).
- [Optimizing SQL queries for speed with dbt @ DataDuel.co](https://www.dataduel.co/optimizing-sql-queries-for-speed-with-dbt/).
- [Test Driven Development (TDD) with dbt: Test First, SQL Later @ Xebia](https://xebia.com/blog/test-driven-development-tdd-with-dbt/).
- [Understanding dbt: basics and best practices @ Datadog](https://www.datadoghq.com/blog/understanding-dbt/).]]>
            </summary>
            <updated>2025-09-08T13:29:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4697</id>
            <title type="text"><![CDATA[Git Query language]]></title>
            <link rel="alternate" href="https://amrdeveloper.github.io/GQL/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4697"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[GQL is a query language with a syntax very similar to SQL with a tiny engine to perform queries on .git files instance of database files, the engine executes the query on the fly without the need to create database files or convert .git files into any other format, note that all Keywords in GQL are case-insensitive similar to SQL.

- [GQL @ GitHub](https://github.com/AmrDeveloper/GQL).]]>
            </summary>
            <updated>2025-08-29T04:59:52+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4796</id>
            <title type="text"><![CDATA[SQLite]]></title>
            <link rel="alternate" href="https://www.sqlite.org/index.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4796"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine.

Related contents:

- [SQLite: How it works, by Richard Hipp @ Prof. Dr. Jens Dittrich, Big Data Analytics&amp;#039; YouTube](https://www.youtube.com/watch?v=ZSKLA81tBis).
- [Optimizing SQLite for servers @ Sylvain Kerkour :fr:](https://kerkour.com/sqlite-for-servers).
- [What you need to know about SQLite @ Joy of Rails](https://joyofrails.com/articles/what-you-need-to-know-about-sqlite).
- [Collection of insane and fun facts about SQLite @ avi.im&amp;#039;s blag](https://avi.im/blag/2024/sqlite-facts/).]]>
            </summary>
            <updated>2025-08-29T05:16:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4797</id>
            <title type="text"><![CDATA[libsql]]></title>
            <link rel="alternate" href="https://turso.tech/libsql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4797"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQLite for modern applications.libSQL is a fork of SQLite that is both Open Source, and Open Contributions. 

libSQL is an open source, open contribution fork of SQLite, created and maintained by Turso. We aim to evolve it to suit many more use cases than SQLite was originally designed for, and plan to use third-party OSS code wherever it makes sense.

- [libSQL @ GitHub](https://github.com/tursodatabase/libsql).]]>
            </summary>
            <updated>2025-08-29T05:16:02+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4798</id>
            <title type="text"><![CDATA[SurrealDB]]></title>
            <link rel="alternate" href="https://surrealdb.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4798"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The ultimate multi-model database. Develop easier. Build faster. Scale quicker.

SurrealDB is an end-to-end cloud-native database designed for modern applications, including web, mobile, serverless, Jamstack, backend, and traditional applications. With SurrealDB, you can simplify your database and API infrastructure, reduce development time, and build secure, performant apps quickly and cost-effectively.

- [SurrealDB @ GitHub](https://github.com/surrealdb/surrealdb).
- [SurrealDB University](https://surrealdb.com/learn).]]>
            </summary>
            <updated>2025-08-29T05:16:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4845</id>
            <title type="text"><![CDATA[jSQL Injection]]></title>
            <link rel="alternate" href="https://github.com/ron190/jsql-injection" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4845"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[jSQL Injection is a Java application for automatic SQL database injection.]]>
            </summary>
            <updated>2025-08-29T05:24:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4869</id>
            <title type="text"><![CDATA[Neon]]></title>
            <link rel="alternate" href="https://neon.tech/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4869"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Serverless, Fault-Tolerant, Branchable Postgres.

The fully managed multi-cloud Postgres with a generous free tier. We separated storage and compute to offer autoscaling, branching, and bottomless storage.

- [Neon @ GitHub](https://github.com/neondatabase/neon).
- [Awesome Neon @ GitHub](https://github.com/tyaga001/awesome-neon).]]>
            </summary>
            <updated>2025-08-29T05:28:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4877</id>
            <title type="text"><![CDATA[The Grand Complete Data Science Guide With Videos And Materials]]></title>
            <link rel="alternate" href="https://github.com/krishnaik06/The-Grand-Complete-Data-Science-Materials" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4877"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Contribute to krishnaik06/The-Grand-Complete-Data-Science-Materials development by creating an account on GitHub.]]>
            </summary>
            <updated>2025-08-29T05:31:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4897</id>
            <title type="text"><![CDATA[GlareDB]]></title>
            <link rel="alternate" href="https://glaredb.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4897"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Data Pipeline, Simplified.  GlareDB: An analytics DBMS for distributed data.

Data exists everywhere: your laptop, Postgres, Snowflake and as files in S3. It exists in various formats such as Parquet, CSV and JSON. Regardless, there will always be multiple steps spanning several destinations to get the insights you need.

GlareDB is designed to query your data wherever it lives using SQL that you already know.

- [GlareDB @ GitHub](https://github.com/GlareDB/glaredb)
- [What the Heck is GlareDB? @ HackerNoon](https://hackernoon.com/what-the-heck-is-glaredb).]]>
            </summary>
            <updated>2025-08-29T05:33:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4950</id>
            <title type="text"><![CDATA[Dolt]]></title>
            <link rel="alternate" href="https://www.dolthub.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4950"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Dolt is Git for data. The world&amp;#039;s first and only version-controlled SQL database.

Dolt is a SQL database that you can fork, clone, branch, merge, push and pull just like a Git repository.

Connect to Dolt just like any MySQL database to read or modify schema and data. Version control functionality is exposed in SQL via system tables, functions, and procedures.

- [Dolt @ GitHub](https://github.com/dolthub/dolt).

Related contents:

- [Hunting a Memory Leak @ DoltHub]().]]>
            </summary>
            <updated>2025-08-29T05:41:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4956</id>
            <title type="text"><![CDATA[trdsql]]></title>
            <link rel="alternate" href="https://noborus.github.io/trdsql/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4956"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[CLI tool that can execute SQL queries on CSV, LTSV, JSON and TBLN. Can output to various formats.

- [trdsql @ GitHub](https://github.com/noborus/trdsql).]]>
            </summary>
            <updated>2025-11-04T07:56:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5021</id>
            <title type="text"><![CDATA[SQLCoder]]></title>
            <link rel="alternate" href="https://github.com/defog-ai/sqlcoder" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5021"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Defog&amp;#039;s SQLCoder is a state-of-the-art LLM for converting natural language questions to SQL queries.]]>
            </summary>
            <updated>2025-08-29T05:53:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5023</id>
            <title type="text"><![CDATA[AgeSQL]]></title>
            <link rel="alternate" href="https://github.com/AGEDB-INC/AgeSQL" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5023"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Graph Database CLI based on PostgreSQL psql.

AgeSQL is a command-line interface (CLI) client for PostgreSQL that extends its capabilities to support Cypher queries along with traditional SQL. This tool leverages the Age extension for PostgreSQL, which enables graph queries within the database.

The aim of AgeSQL is to create a CLI tool that operates similarly to the existing PostgreSQL CLI (psql) and provides complete functionality for working with graph databases. In addition, AgeSQL wraps Cypher commands to simplify their usage within PostgreSQL.]]>
            </summary>
            <updated>2025-08-29T05:55:19+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5079</id>
            <title type="text"><![CDATA[ProxySQL]]></title>
            <link rel="alternate" href="https://proxysql.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5079"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A High Performance Open Source MySQL Proxy.

ProxySQL is an open source high performance, high availability, database protocol aware proxy for MySQL

- [ProxySQL @ GitHub](https://github.com/sysown/proxysql).
- [Early MySQL engineer questions whether Oracle is unintentionally killing off the open source database @ The Register](https://www.theregister.com/2024/06/11/early_mysql_engineer_questions_whether/)]]>
            </summary>
            <updated>2025-08-29T06:03:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5083</id>
            <title type="text"><![CDATA[Turso]]></title>
            <link rel="alternate" href="https://turso.tech/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5083"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQLite Developer Experience in an Edge Database.

Turso is an edge-hosted, distributed database based on libSQL, an open-source and open-contribution fork of SQLite. It was designed to minimize query latency for applications where queries come from anywhere in the world. In particular, it works well with edge functions provided by cloud platforms such as CloudFlare, Netlify, and Vercel, by putting your data geographically close to the code that accesses it.

- [Turso Database @ GitHub](https://github.com/tursodatabase/turso).
- [libSQL @ GitHub](https://github.com/tursodatabase/libsql).

Related contents:

- [Local RAG with Ollama, Mistral, and Turso @ Turso&amp;#039;s blog](https://turso.tech/blog/local-rag-with-ollama-and-turso-sqlite).
- [Deep dive into Turso, the &amp;quot;SQLite rewrite in Rust&amp;quot; @ Sylvain Kerkour](https://kerkour.com/turso-sqlite).]]>
            </summary>
            <updated>2026-01-30T12:45:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5084</id>
            <title type="text"><![CDATA[DrizzleORM]]></title>
            <link rel="alternate" href="https://orm.drizzle.team/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5084"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[TypeScript ORM that feels like writing SQL.

Drizzle ORM is a TypeScript ORM for SQL databases designed with maximum type safety in mind. It comes with a drizzle-kit CLI companion for automatic SQL migrations generation. Drizzle ORM is meant to be a library, not a framework. It stays as an opt-in solution all the time at any levels. The ORM&amp;#039;s main philosophy is &amp;quot;If you know SQL, you know Drizzle ORM&amp;quot;. We follow the SQL-like syntax whenever possible, are strongly typed ground up, and fail at compile time, not in runtime.

[DrizzleORM @ GitHub](https://github.com/drizzle-team/drizzle-orm).]]>
            </summary>
            <updated>2025-08-29T06:04:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5256</id>
            <title type="text"><![CDATA[SchemaCrawler]]></title>
            <link rel="alternate" href="https://www.schemacrawler.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5256"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Free database schema discovery and comprehension tool.]]>
            </summary>
            <updated>2025-08-29T06:32:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5257</id>
            <title type="text"><![CDATA[ERDPlus]]></title>
            <link rel="alternate" href="https://erdplus.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5257"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A database modeling tool for creating Entity Relationship Diagrams, Relational Schemas, Star Schemas, and SQL DDL statements.]]>
            </summary>
            <updated>2025-08-29T06:32:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5260</id>
            <title type="text"><![CDATA[dbt]]></title>
            <link rel="alternate" href="https://www.getdbt.com/product/what-is-dbt/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5260"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[dbt™ is a SQL-first transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone on the data team can safely contribute to production-grade data pipelines.

[dbt @ GitHub](https://github.com/dbt-labs/dbt-core).]]>
            </summary>
            <updated>2025-08-29T06:33:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5297</id>
            <title type="text"><![CDATA[QuestDB]]></title>
            <link rel="alternate" href="https://questdb.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5297"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fast SQL for time-series



QuestDB is an open-source time-series database for high throughput ingestion and fast SQL queries with operational simplicity. It supports schema-agnostic ingestion using the InfluxDB line protocol, PostgreSQL wire protocol, and a REST API for bulk imports and exports.

[QuestDB @ GitHub](https://github.com/questdb/questdb).]]>
            </summary>
            <updated>2025-08-29T06:39:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5330</id>
            <title type="text"><![CDATA[SQLPage]]></title>
            <link rel="alternate" href="https://sql.ophir.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5330"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source low-code web application framework. Create full websites writing only simple database queries.

SQLpage is an SQL-only webapp builder. It is meant for data scientists, analysts, and business intelligence teams to build powerful data-centric applications quickly, without worrying about any of the traditional web programming languages and concepts.

With SQLPage, you write simple .sql files containing queries to your database to select, group, update, insert, and delete your data, and you get good-looking clean webpages displaying your data as text, lists, grids, plots, and forms.

[SQLPage @ GitHub](https://github.com/lovasoa/SQLPage).]]>
            </summary>
            <updated>2025-08-29T06:45:44+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5365</id>
            <title type="text"><![CDATA[Laravel MySQL Explains For Humans]]></title>
            <link rel="alternate" href="https://github.com/tpetry/laravel-mysql-explain" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5365"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Get MySQL EXPLAIN plans that are understandable for humans.

MySQL Query optimization with the EXPLAIN command is unnecessarily complicated: The output contains a lot of cryptic information that is incomprehensible or entirely misleading.

This Laravel package collects many query metrics that will be sent to explainmysql.com and transformed to be much easier to understand.]]>
            </summary>
            <updated>2025-08-29T06:51:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5416</id>
            <title type="text"><![CDATA[MySQL EXPLAIN Explained]]></title>
            <link rel="alternate" href="https://explainmysql.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5416"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[You no longer have to search for cryptic or incomprehensible information from MySQL query plans. All EXPLAIN outputs are transformed into data that is easier to grasp.]]>
            </summary>
            <updated>2025-08-29T06:59:56+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5594</id>
            <title type="text"><![CDATA[OverAPI.com]]></title>
            <link rel="alternate" href="https://overapi.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5594"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Collecting all the cheat sheets]]>
            </summary>
            <updated>2025-08-29T07:29:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5679</id>
            <title type="text"><![CDATA[Pyrseas]]></title>
            <link rel="alternate" href="https://github.com/perseas/Pyrseas" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5679"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Provides utilities for Postgres database schema versioning.
Pyrseas provides utilities to describe a PostgreSQL database schema as YAML, to verify the schema against the same or a different database and to generate SQL that will modify the schema to match the YAML description.]]>
            </summary>
            <updated>2025-08-29T07:44:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5872</id>
            <title type="text"><![CDATA[Mockaroo]]></title>
            <link rel="alternate" href="https://mockaroo.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5872"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Random Data Generator and API Mocking Tool (JSON / CSV / SQL / Excel).

Need some mock data to test your app? Mockaroo lets you generate up to 1,000 rows of realistic test data in CSV, JSON, SQL, and Excel formats.]]>
            </summary>
            <updated>2025-08-29T08:16:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6155</id>
            <title type="text"><![CDATA[csvkit]]></title>
            <link rel="alternate" href="https://csvkit.readthedocs.io/en/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6155"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[csvkit is a suite of command-line tools for converting to and working with CSV, the king of tabular file formats.

- [csvkit @ GitHub](https://github.com/wireservice/csvkit)]]>
            </summary>
            <updated>2025-11-04T07:24:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6215</id>
            <title type="text"><![CDATA[PRQL]]></title>
            <link rel="alternate" href="https://prql-lang.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6215"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Pipelined Relational Query Language, pronounced &amp;quot;Prequel&amp;quot;.
PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement. Like SQL, it&amp;#039;s readable, explicit and declarative. Unlike SQL, it forms a logical pipeline of transformations, and supports abstractions such as variables and functions. It can be used with any database that uses SQL, since it compiles to SQL.

[PRQL @ GitHub](https://github.com/PRQL/prql)]]>
            </summary>
            <updated>2025-08-29T09:13:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6252</id>
            <title type="text"><![CDATA[Beekeeper Studio]]></title>
            <link rel="alternate" href="https://www.beekeeperstudio.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6252"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The SQL Editor and Database Manager Of Your Dreams.
A modern, easy to use, and good looking SQL client for MySQL, Postgres, SQLite, SQL Server, and more.]]>
            </summary>
            <updated>2025-08-29T09:19:04+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6382</id>
            <title type="text"><![CDATA[DuckDB]]></title>
            <link rel="alternate" href="https://duckdb.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6382"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[DuckDB is an in-process SQL OLAP database management system.

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL
DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and several extensions designed to make SQL easier to use.

- [DuckDB @ GitHub](https://github.com/duckdb/duckdb).

Related contents:

- [DuckDB - Le moteur SQL qui transforme vos données @ Korben :fr:](https://korben.info/duckdb-moteur-sql-transformation-donnees.html).
- [Why DuckDB is my first choice for data processing @ \&amp;gt;robinlinacre](https://www.robinlinacre.com/recommend_duckdb/#why-duckdb-is-my-first-choice-for-data-processing).
- [DuckDB is Probably the Most Important Geospatial Software of the Last Decade @ dbreunig.com](https://www.dbreunig.com/2025/05/03/duckdb-is-the-most-impactful-geospatial-software-in-a-decade.html).
- [Why Semantic Layers Matter — and How to Build One with DuckDB @ MotherDuck](https://motherduck.com/blog/semantic-layer-duckdb-tutorial/).
- [Querying Billions of GitHub Events Using Modal and DuckDB (Part 1: Ingesting Data) @ noreasontopanic](https://noreasontopanic.com/p/querying-billions-of-github-events).
- [DuckDB beats Polars for 1TB of data @ Confessions of a Data Guy](https://www.confessionsofadataguy.com/duckdb-beats-polars-for-1tb-of-data/).
- [Building Your Modern Data Analytics Stack with Python, Parquet, and DuckDB @ KD nuggets](https://www.kdnuggets.com/building-your-modern-data-analytics-stack-with-python-parquet-and-duckdb).
- [Building an Obsidian RAG with DuckDB and MotherDuck @ MotherDuck](https://motherduck.com/blog/obsidian-rag-duckdb-motherduck/).
- [DuckDB Internals: Why is DuckDB Fast? (Part 1) @ Greybeam](https://www.greybeam.ai/blog/duckdb-internals-part-1).]]>
            </summary>
            <updated>2026-06-22T06:30:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6397</id>
            <title type="text"><![CDATA[FerretDB]]></title>
            <link rel="alternate" href="https://www.ferretdb.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6397"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A truly Open Source MongoDB alternative.
FerretDB (previously MangoDB) was founded to become the de-facto open-source substitute to MongoDB. FerretDB is an open-source proxy, converting the MongoDB 6.0+ wire protocol queries to SQL - using PostgreSQL as a database engine.

- [FerretDB @ GitHub](https://github.com/FerretDB/FerretDB).

Related contents:

- [Microsoft builds open source document database on PostgreSQL, suggests FerretDB as front end @ The Register](https://www.theregister.com/2025/01/27/microsoft_builds_open_source_document/).
- [Building for Developers—Not Imitators @ MongoDB](https://www.mongodb.com/company/blog/building-for-developers-not-imitators).
- [Oxygen Deprivation: FerretDB with Peter Farkas @ Contributor.fyi](https://www.contributor.fyi/ferretdb).
- [FerretDB Was Eating My CPU: Migrating Komodo from SQLite to Postgres @ mauveRANT](https://rant.mvh.dev/ferretdb-was-eating-my-cpu-migrating-komodo-from-sqlite-to-postgres/).]]>
            </summary>
            <updated>2026-03-29T19:27:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6631</id>
            <title type="text"><![CDATA[MindsDB]]></title>
            <link rel="alternate" href="https://github.com/mindsdb/mindsdb" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6631"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[In-Database Machine Learning.
MindsDB ML-SQL Server enables machine learning workflows for the most powerful databases and data warehouses using SQL.]]>
            </summary>
            <updated>2025-08-29T10:22:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6935</id>
            <title type="text"><![CDATA[DBeaver]]></title>
            <link rel="alternate" href="https://dbeaver.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6935"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Free multi-platform database tool for developers, database administrators, analysts and all people who need to work with databases. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, MS Access, Teradata, Firebird, Apache Hive, Phoenix, Presto, etc.]]>
            </summary>
            <updated>2025-08-29T11:14:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6979</id>
            <title type="text"><![CDATA[PGLoader]]></title>
            <link rel="alternate" href="https://pgloader.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6979"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Migrate to PostgreSQL in a single command!

pgloader loads data into PostgreSQL and allows you to implement Continuous Migration from your current database to PostgreSQL. Read the White Paper to learn how to limit risks and control your budget, and start your PostgreSQL migration today!

[PGLoader @ GitHub](https://github.com/dimitri/pgloader)]]>
            </summary>
            <updated>2025-08-29T11:20:10+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6980</id>
            <title type="text"><![CDATA[NMIG]]></title>
            <link rel="alternate" href="https://github.com/AnatolyUss/nmig" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6980"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[NMIG is a database migration tool, written in Node.js and highly inspired by FromMySqlToPostgreSql.
NMIG is an app, intended to make a process of migration from MySQL to PostgreSQL as easy and smooth as possible.]]>
            </summary>
            <updated>2025-08-29T11:20:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7147</id>
            <title type="text"><![CDATA[Prisma]]></title>
            <link rel="alternate" href="https://www.prisma.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7147"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Next-generation Node.js and TypeScript ORM for Databases.
Prisma helps app developers build faster and make fewer errors with an open source database toolkit for PostgreSQL, MySQL, SQL Server, and SQLite.

- [Prisma @ GitHub](https://github.com/prisma).

Related contents:

- [Guide complet de Prisma avec NextJS @ codelynx.dev :fr:](https://codelynx.dev/posts/102-guide-prisma).]]>
            </summary>
            <updated>2025-08-29T11:48:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7195</id>
            <title type="text"><![CDATA[Arctype SQL Client]]></title>
            <link rel="alternate" href="https://arctype.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7195"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQL Editor for Developers.
The SQL client and database
management tool that&amp;#039;s fun to use]]>
            </summary>
            <updated>2025-08-29T11:56:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7471</id>
            <title type="text"><![CDATA[Record Query]]></title>
            <link rel="alternate" href="https://github.com/dflemstr/rq" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7471"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[It&amp;#039;s a tool that&amp;#039;s used for performing queries on streams of records in various formats.

The goal is to make ad-hoc exploration of data sets easy without having to use more heavy-weight tools like SQL/MapReduce/custom programs. rq fills a similar niche as tools like awk or sed, but works with structured (record) data instead of text.

It was created with love out of the best parts of Rust, C and Javascript, and is distributed as a dependency-free binary on many operating systems and architectures.]]>
            </summary>
            <updated>2025-08-29T12:42:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7721</id>
            <title type="text"><![CDATA[Bouquet]]></title>
            <link rel="alternate" href="http://openbouquet.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7721"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source analytics toolbox

Analyze your data without writing a line of SQL.]]>
            </summary>
            <updated>2025-08-29T13:24:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7825</id>
            <title type="text"><![CDATA[SQLmap]]></title>
            <link rel="alternate" href="http://sqlmap.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7825"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[automatic SQL injection and database takeover tool.

SQLmap is an open source penetration testing tool that automates the process of detecting and exploiting SQL injection flaws and taking over of database servers.

- [SQLmap @ GitHub](https://github.com/sqlmapproject/sqlmap).
- [How To Attack Sql Injection Using [SQLMAP] Via Method [POST] @ System Weakness](https://systemweakness.com/how-to-attack-sql-injection-using-sqlmap-via-method-post-cae19495319f).]]>
            </summary>
            <updated>2025-08-29T13:41:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/8091</id>
            <title type="text"><![CDATA[SQL Fiddle]]></title>
            <link rel="alternate" href="http://www.sqlfiddle.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/8091"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Analyseur de requête SQL]]>
            </summary>
            <updated>2025-08-29T14:25:54+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/8467</id>
            <title type="text"><![CDATA[TextQL]]></title>
            <link rel="alternate" href="https://github.com/dinedal/textql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/8467"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Allows you to easily execute SQL against structured text like CSV or TSV.]]>
            </summary>
            <updated>2025-08-29T15:28:36+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/8706</id>
            <title type="text"><![CDATA[SchemaSpy]]></title>
            <link rel="alternate" href="http://schemaspy.sourceforge.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/8706"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SchemaSpy is a Java-based tool (requires Java 5 or higher) that analyzes the metadata of a schema in a database and generates a visual representation of it in a browser-displayable format. It lets you click through the hierarchy of database tables via child and parent table relationships as represented by both HTML links and entity-relationship diagrams. It&amp;#039;s also designed to help resolve the obtuse errors that a database sometimes gives related to failures due to constraints.]]>
            </summary>
            <updated>2025-08-29T16:08:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/9029</id>
            <title type="text"><![CDATA[sqlcake | automatic sql injection exploitation kit]]></title>
            <link rel="alternate" href="http://sqlcake.sourceforge.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/9029"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[sqlcake is an automatic SQL injection exploitation kit written in Ruby. It&amp;#039;s designed for system administration and penetration testing.]]>
            </summary>
            <updated>2025-08-29T17:02:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/9837</id>
            <title type="text"><![CDATA[SQuirreL SQL Client Home Page]]></title>
            <link rel="alternate" href="http://www.squirrelsql.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/9837"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SQuirreL SQL is an open-source Java SQL Client program for any JDBC compliant database]]>
            </summary>
            <updated>2025-08-29T19:18:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/9913</id>
            <title type="text"><![CDATA[Drizzle]]></title>
            <link rel="alternate" href="http://drizzle.org/Home.html" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/9913"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This domain name has been registered with Gandi.net. It is currently parked by the owner.]]>
            </summary>
            <updated>2025-08-29T19:30:40+00:00</updated>
        </entry>
    </feed>
