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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A transactional, relational-graph-vector database that uses Datalog for query. The hippocampus for AI!
| Date | Stars |
|---|---|
| 2026-07-31 | 4072 |
| 2026-08-03 | 4072 |
| 2026-08-06 | 4076 |
Today
+4 stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<img src="static/logo_c.png" width="200" height="175" alt="Logo"> [](https://docs.cozodb.org/) [](https://www.npmjs.com/package/cozo-node) [](https://www.npmjs.com/package/cozo-lib-wasm) [](https://crates.io/crates/cozo) [](https://docs.rs/cozo) [](https://pypi.org/project/pycozo/) [](https://mvnrepository.com/artifact/io.github.cozodb/cozo_java) [](https://mvnrepository.com/artifact/io.github.cozodb/cozo-clj) [](https://mvnrepository.com/artifact/io.github.cozodb/cozo_android) [](https://github.com/cozodb/cozo/tree/main/cozo-lib-swift) [](https://github.com/cozodb/cozo-lib-go) [](https://github.com/cozodb/cozo/releases) [](https://github.com/cozodb/cozo/actions/workflows/build.yml) [](https://github.com/cozodb/cozo/blob/main/LICENSE.txt) # `CozoDB` ### Table of contents 1. [Introduction](#Introduction) 2. [Getting started](#Getting-started) 3. [Install](#Install) 4. [Architecture](#Architecture) 5. [Status of the project](#Status-of-the-project) 6. [Links](#Links) 7. [Licensing and contributing](#Licensing-and-contributing) ## 🎉🎉🎉 New versions 🎉🎉🎉 Version v0.7: after HNSW vector search from 0.6, in 0.7 we bring to you MinHash-LSH for near-duplicate search, full-text search, Json value support and more! See [here](https://docs.cozodb.org/en/latest/releases/v0.7.html) for more details. --- Version v0.6 released! This version brings vector search with HNSW indices inside Datalog, which can be integrated seamlessly with powerful features like ad-hoc joins, recursive Datalog and classical whole-graph algorithms. This significantly expanded the horizon of possibilities of CozoDB. Highlights: * You can now create HNSW (hierarchical navigable small world) indices on relations containing vectors. * You can create multiple HNSW indices for the same relation by specifying filters dictating which rows should be indexed, or which vector(s) should be indexed for each row if the row contains multiple vectors. * The vector search functionality is integrated within Datalog, meaning that you can use vectors (either explicitly given or coming from another relation) as pivots to perform unification into the indexed relations (roughly equivalent to table joins in SQL). * Unification with vector search is semantically no different from regular unification, meaning that you can even use vector search in recursive Datalog, enabling extremely complex query logic. * The HNSW index is no more than a hierarchy of proximity graphs. As an open, competent graph database, CozoDB exposes these graphs to the end user to be used as regular graphs in your query, so that all the usual techniques for dealing with them can now be applied, especially: community detection and other classical whole-graph algorithms. * As with all mutations in CozoDB, the index is protected from corruption in the face of concurrent writes by using Multi-Version Concurrency Control (MVCC), and you can use multi-statement transactions for complex workflows. * The index resides on disk as a regular relation (unle
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Ziyang Hu
1.7k
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Diwank Singh Tomer · @julep-ai
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Michael Bradley
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Sean Lynch · United States
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Niwaka · Japan
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:f0ae9a7ff883d461, desc:vector database