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    <title>vector-data</title>
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    <updated>2026-08-13T18:30:30+00:00</updated>
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            <entry>
            <id>https://links.biapy.com/links/13620</id>
            <title type="text"><![CDATA[DiskANN]]></title>
            <link rel="alternate" href="https://github.com/microsoft/DiskANN" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/13620"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A vector indexing library to bring fast, fresh and filtered search to your database.

DiskANN3 is a composable library for bringing scalable, accurate and cost-effective vector indexing to multiple databases. It draws on research from the DiskANN project.

Related contents:

- [653: Microsoft&amp;#039;s Franck Pachot @ Coder Radio](https://coder.show/653).]]>
            </summary>
            <updated>2026-08-13T06:13:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12042</id>
            <title type="text"><![CDATA[ReMe]]></title>
            <link rel="alternate" href="https://github.com/agentscope-ai/ReMe" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12042"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Memory Management Kit for Agents - Remember Me, Refine Me. 

🧠 ReMe is a memory management framework built for AI agents, offering both file-based and vector-based memory systems.

It addresses two core problems of agent memory: limited context windows (early information gets truncated or lost during long conversations) and stateless sessions (new conversations cannot inherit history and always start from scratch).

ReMe gives agents real memory — old conversations are automatically condensed, important information is persisted, and the next conversation can recall it automatically.]]>
            </summary>
            <updated>2026-03-06T12:47:50+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/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/4827</id>
            <title type="text"><![CDATA[Lantern]]></title>
            <link rel="alternate" href="https://lantern.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4827"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The most powerful vector database for building AI applications. Open-source PostgreSQL database extension for vector data and vector search operations.

Lantern is an open-source PostgreSQL database extension to store vector data, generate embeddings, and handle vector search operations.

- [Lantern @ GitHub](https://github.com/lanterndata/lantern).]]>
            </summary>
            <updated>2025-08-29T05:21:04+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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