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    <title>cdc</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/1010/feed"/>
    <updated>2026-06-28T01:00:21+00:00</updated>
    <id>https://links.biapy.com/guest/tags/1010/feed</id>
            <entry>
            <id>https://links.biapy.com/links/10721</id>
            <title type="text"><![CDATA[Code-First CDC to ClickHouse with Debezium, Redpanda, and MooseStack]]></title>
            <link rel="alternate" href="https://github.com/514-labs/debezium-cdc" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10721"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Easy-to-run demo of a CDC pipeline using Debezium (Kafka Connect), PostgreSQL, Redpanda, and ClickHouse.]]>
            </summary>
            <updated>2025-10-20T06:22:14+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10426</id>
            <title type="text"><![CDATA[RisingWave]]></title>
            <link rel="alternate" href="https://risingwave.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10426"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Real-Time Event Streaming Platform.
Streaming CDC, stream processing, low-latency serving, and Iceberg management. 

RisingWave is a real-time event streaming platform designed to offer the simplest and most cost-effective way to process, analyze, and manage real-time event data — with built-in support for the Apache Iceberg™ open table format. It provides both a Postgres-compatible SQL interface and a DataFrame-style Python interface.

RisingWave can ingest millions of events per second, continuously join and analyze live streams with historical data, serve ad-hoc queries at low latency, and persist fresh, consistent results to Apache Iceberg™ or any other downstream system.

- [RisingWave @ GitHub](https://github.com/risingwavelabs/risingwave).

Related contents:

- [The Case for Hybrid Cache for Object Stores @ Data Engineer Things&amp;#039; Medium](https://blog.dataengineerthings.org/the-case-for-hybrid-cache-for-object-stores-4b1f02ec6c9a).
- [You Gotta Push If You Wanna Pull @ Gunnar Morling](https://www.morling.dev/blog/you-gotta-push-if-you-wanna-pull/).]]>
            </summary>
            <updated>2025-12-08T13:43:05+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1110</id>
            <title type="text"><![CDATA[OLake]]></title>
            <link rel="alternate" href="https://olake.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1110"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fastest way to Replicate your Database data in Data Lake.
OLake makes data replication faster by parallelizing full loads, leveraging change streams for real-time sync, and pulling data in a database-native format for efficient ingestion.

Fastest open-source tool for replicating Databases to Apache Iceberg or Data Lakehouse. ⚡ Efficient, quick and scalable data ingestion for real-time analytics. Supporting Postgres, MongoDB and MySQL 

- [OLake @ GitHub](https://github.com/datazip-inc/olake).

Related contents:

- [Change Data Capture Tools @ Dev Genius&amp;#039; Medium](https://blog.devgenius.io/change-data-capture-tools-c0e4ee4434ac).]]>
            </summary>
            <updated>2025-08-28T19:02:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1113</id>
            <title type="text"><![CDATA[Sequin]]></title>
            <link rel="alternate" href="https://sequinstream.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1113"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The fastest Postgres change data capture.

Stream data from Postgres directly to Kafka, Redis, and more. Replace complex tools like Debezium and consolidate workflows. 

- [Sequin @ GitHub](https://github.com/sequinstream/sequin).

Related contents:

- [Change Data Capture Tools @ Dev Genius&amp;#039; Medium](https://blog.devgenius.io/change-data-capture-tools-c0e4ee4434ac).]]>
            </summary>
            <updated>2025-08-28T19:02:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1114</id>
            <title type="text"><![CDATA[Maxwell&amp;#039;s Daemon]]></title>
            <link rel="alternate" href="https://maxwells-daemon.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1114"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[This is Maxwell&amp;#039;s daemon, a change data capture application that reads MySQL binlogs and writes data changes as JSON to Kafka, Kinesis, and other streaming platforms.

- [Maxwell&amp;#039;s Daemon @ GitHub](https://github.com/zendesk/maxwell).

Related contents:

- [Change Data Capture Tools @ Dev Genius&amp;#039; Medium](https://blog.devgenius.io/change-data-capture-tools-c0e4ee4434ac).]]>
            </summary>
            <updated>2025-08-28T19:02:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1115</id>
            <title type="text"><![CDATA[DBConvert Streams]]></title>
            <link rel="alternate" href="https://docs.dbconvert.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1115"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Migrate Databases and Stream Data Between Database Systems.

DBConvert Streams (DBS) is a cutting-edge distributed platform designed for data migration between heterogeneous databases and real-time data replication. It simplifies the process of transferring data between on-premises or cloud databases, including relational databases and data warehouses.

- [DBConvert Streams @ GitHub](https://github.com/slotix/dbconvert-streams-public).

Related contents:

- [Change Data Capture Tools @ Dev Genius&amp;#039; Medium](https://blog.devgenius.io/change-data-capture-tools-c0e4ee4434ac).]]>
            </summary>
            <updated>2025-08-28T19:02:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1462</id>
            <title type="text"><![CDATA[PeerDB]]></title>
            <link rel="alternate" href="https://www.peerdb.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1462"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage.

PeerDB is an ETL/ELT tool built for PostgreSQL. We implement multiple Postgres native and infrastructural optimizations to provide a fast, reliable and a feature-rich experience for moving data in/out of PostgreSQL.

- [PeerDB @ GitHub](https://github.com/PeerDB-io/peerdb).

Related contents:

- [Reliably Replicating Data Between PostgreSQL and ClickHouse Part 1 - PeerDB Open Source @ BenjaminWootton.com](https://benjaminwootton.com/insights/clickhouse-peerdb-cdc/).
- [Postgres Is the Gateway Drug @ Vignesh Ravichandran](https://viggy28.dev/article/postgres-gateway-drug/).]]>
            </summary>
            <updated>2026-03-23T16:36:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2688</id>
            <title type="text"><![CDATA[Debezium]]></title>
            <link rel="alternate" href="https://debezium.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2688"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Debezium is an open source distributed platform for change data capture. Start it up, point it at your databases, and your apps can start responding to all of the inserts, updates, and deletes that other apps commit to your databases. Debezium is durable and fast, so your apps can respond quickly and never miss an event, even when things go wrong. 

- [Debezium @ GitHub](https://github.com/debezium/debezium).

Related contents:

- [Code first CDC from Postgres to ClickHouse with Debezium, Redpanda, and MooseStack @ Fileonefour](https://www.fiveonefour.com/blog/cdc-postgres-to-clickhouse-debezium-drizzle)
  ([Code-First CDC to ClickHouse with Debezium, Redpanda, and MooseStack @ GitHub](https://github.com/514-labs/debezium-cdc)).
- [Change Data Capture Tools @ Dev Genius&amp;#039; Medium](https://blog.devgenius.io/change-data-capture-tools-c0e4ee4434ac).
- [The Equality Delete Problem in Apache Iceberg @ Data Engineer Things&amp;#039; Medium](https://blog.dataengineerthings.org/the-equality-delete-problem-in-apache-iceberg-143dd451a974).
- [You Gotta Push If You Wanna Pull @ Gunnar Morling](https://www.morling.dev/blog/you-gotta-push-if-you-wanna-pull/).
- [Keep your cache always fresh with Debezium! (Current 22) @ SpeakerDeck](https://speakerdeck.com/gunnarmorling/keep-your-cache-always-fresh-with-debezium-current-22).
- [A Deep Dive Into Ingesting Debezium Events From Kafka With Flink SQL @ Gunnar Morling](https://www.morling.dev/blog/ingesting-debezium-events-from-kafka-with-flink-sql/).
- [The challenges of soft delete @ atlas9 blog](https://atlas9.dev/blog/soft-delete.html).]]>
            </summary>
            <updated>2026-01-21T13:11:25+00:00</updated>
        </entry>
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