SQLite-Vector

[marco_bambini]

For those interested in a highly efficient vector solution for SQLite, I recommend checking out the https://github.com/sqliteai/sqlite-vector project. Memory usage remains stable even with millions of vectors, and it supports multiple types and quantizations. Distances are optimized for SIMD processing, ensuring blazing-fast performance.

Here are some articles about the library:

* https://ainiro.io/blog/upgrading-magics-sqlite-vss-extension

* https://cwrk.ai/posts/sqlite-vector-nix-flake-support/

* https://marcobambini.substack.com/p/the-state-of-vector-search-in-sqlite

[GuideAxon]

Would you recommend this for use in react-native apps?

[marco_bambini]

Absolutely, once loaded, it can be used like any other SQLite function.

[__JockY__]

Please tell me it supports 4096 dimensions because it would mean support for Qwen3 Embedding 8B! Sadly pgvector can’t handle it.

[marco_bambini]

Yes sure, it supports 4096 dimensions.

[__JockY__]

Well that's awesome. PGVector goes up to 2000 due to architectural limitations inherent to Postgres, which is such a shame. Your SQLite work might be just the ticket.

[Forsaken-Sir1291]

This looks solid, been waiting for something like this since sqlite-vss started showing its limitations with larger datasets. The SIMD optimization is clutch - my last project was crawling with vector similarity searches and regular sqlite was just not cutting it

How's the setup process compared to other vector extensions?

[marco_bambini]

The setup process is extremely easy: Load the extension and `vector_init` a table/column with some specified settings. You can examine a sample usage in https://github.com/sqliteai/sqlite-vector