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    <title>vector-database</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/574/feed"/>
    <updated>2026-04-19T09:18:15+00:00</updated>
    <id>https://links.biapy.com/guest/tags/574/feed</id>
            <entry>
            <id>https://links.biapy.com/links/12275</id>
            <title type="text"><![CDATA[OpenData]]></title>
            <link rel="alternate" href="https://www.opendata.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12275"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Object-store native databases built on a common foundation. Simple to operate. Impossible to outgrow. 

OpenData is a collection of open source databases built on a common, object-native storage and infrastructure foundation. This shared foundation means every database has a virtually identical operational profile, which makes our database fleet materially easier and cheaper to operate than alternatives.

- [OpenData @ GitHub](https://github.com/opendata-oss/opendata).

Related contents:

- [the broken economics of databases @ bits&amp;amp;pages](https://www.bitsxpages.com/p/the-broken-economics-of-databases).]]>
            </summary>
            <updated>2026-03-24T13:28:17+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11922</id>
            <title type="text"><![CDATA[RuVector]]></title>
            <link rel="alternate" href="https://github.com/ruvnet/ruvector" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11922"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The vector database that gets smarter the more you use it — and now ships as a cognitive container.

RuVector is a High Performance, Real-Time, Self-Learning, Vector Graph Neural Network, and Database built in Rust. 

Most vector databases are static — they store embeddings and search them. That&amp;#039;s it. RuVector is different: it learns from every query, runs LLMs locally, scales horizontally, boots as a Linux microservice from a single file, and costs nothing to operate.]]>
            </summary>
            <updated>2026-02-25T12:43:40+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11850</id>
            <title type="text"><![CDATA[Zvec]]></title>
            <link rel="alternate" href="https://zvec.org/en/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11850"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A lightweight, lightning-fast, in-process vector database
High-Performance semantic search, made simple.

Zvec is an open-source, in-process vector database — lightweight, lightning-fast, and designed to embed directly into applications. Built on Proxima (Alibaba&amp;#039;s battle-tested vector search engine), it delivers production-grade, low-latency, scalable similarity search with minimal setup.

- [Zvec @ GitHub](https://github.com/alibaba/zvec).

Related contents:

- [\#129 - News Mars 2026, Vite+, Void Cloud, du drama et de l&amp;#039;IA @ Double Slash :fr:](https://double-slash.dev/podcasts/news-mars26/).]]>
            </summary>
            <updated>2026-03-20T07:22:09+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11673</id>
            <title type="text"><![CDATA[VectorDBZ]]></title>
            <link rel="alternate" href="https://vectordbz.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11673"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Vector Database Management &amp;amp; Analysis Tool.
Desktop Application for Vector Database Management &amp;amp; Analysis.

Connect to Qdrant, Weaviate, Milvus, ChromaDB, Pinecone, pgvector (PostgreSQL), Elasticsearch, and more. Explore collections, analyze embeddings, and visualize your data—all from a unified interface.

- [VectorDBZ @ GitHub](https://github.com/vectordbz/vectordbz).

Related contents:

- [VectorDBZ - Gérez toutes vos bases vectorielles depuis une seule app @ Korben :fr:](https://korben.info/vectordbz-gestion-bases-vectorielles.html).]]>
            </summary>
            <updated>2026-02-02T08:32:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10334</id>
            <title type="text"><![CDATA[Pinecone]]></title>
            <link rel="alternate" href="https://www.pinecone.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10334"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The vector database to build knowledgeable AI.

The vector database for machine learning applications. Build vector-based personalization, ranking, and search systems that are accurate, fast, and scalable.

Related contents:

- [Building a Hybrid Search RAG System with Pinecone and LangChain @ Arpan Roy&amp;#039;s Medium](https://medium.com/@arpanroy_43094/building-a-hybrid-search-ragsystem-with-pinecone-and-langchain-efed2cbf1f88).]]>
            </summary>
            <updated>2025-09-22T07:00:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10046</id>
            <title type="text"><![CDATA[LEANN]]></title>
            <link rel="alternate" href="https://github.com/yichuan-w/LEANN" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10046"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device. 

LEANN is an innovative vector database that democratizes personal AI. Transform your laptop into a powerful RAG system that can index and search through millions of documents while using 97% less storage than traditional solutions without accuracy loss.

Related contents:

- [LEANN - L&amp;#039;IA personnelle qui écrase 97% de ses concurrents (en taille) @ Korben :fr:](https://korben.info/leann-rag.html).]]>
            </summary>
            <updated>2025-09-08T10:28:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/417</id>
            <title type="text"><![CDATA[Weaviate]]></title>
            <link rel="alternate" href="https://weaviate.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/417"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

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

Related contents:

- [37 Things I Learned About Information Retrieval in Two Years at a Vector Database Company @ Leonie Monigatti](https://www.leoniemonigatti.com/blog/what_i_learned.html).]]>
            </summary>
            <updated>2025-08-28T17:06:49+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5910</id>
            <title type="text"><![CDATA[Qdrant - Vector Search Engine]]></title>
            <link rel="alternate" href="https://qdrant.tech/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5910"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Qdrant (read: quadrant ) is a vector similarity search engine and vector database. It provides a production-ready service with a convenient API to store, search, and manage points - vectors with an additional payload. Qdrant is tailored to extended filtering support. It makes it useful for all sorts of neural-network or semantic-based matching, faceted search, and other applications.

- [Qdrant @ GitHub](https://github.com/qdrant/qdrant).

Related contents:

- [270 - DB Vectorielle - Noé Achache @ &amp;lt;ifttd&amp;gt; :fr:](https://www.ifttd.io/episodes/db-vectorielle).
- [Episode 641: Qdrant&amp;#039;s Brian O&amp;#039;Grady @ Coder Radio](https://coder.show/641).]]>
            </summary>
            <updated>2026-03-12T19:36:11+00:00</updated>
        </entry>
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