Looks really nice, but the only concern I had — how does the perf compare to more mature libraries like faiss?
That being said, ~generally~ I'd say it's faster than using numpy and tools like txtai/chromadb. Faiss and hnswlib (bruteforce) are faster because they store everything in memory and use multiple threads. But for smaller vector indexes, I don't think you'd notice much of a difference. sqlite-vec has some support for SIMD operations, which speeds things up quite a bit, but Faiss still takes the cake.
I wouldn't consider it a "this or that" decision. While txtai does combine Faiss and SQLite, it could also utilize this extension. The same task was just done for Postgres + pgvector. txtai is not tied to any particular backend components.
That being said, txtai offers way more than sqlite-vec, like builtin embedding models and other nice LLM features, so it's definitely apples to oranges.
With this, what DuckDB just added and pgvector, we're seeing a blurring of the lines. Back in 2021, there wasn't a RDBMS that had native vector support. But native vector integration makes it possible for txtai to just run SQL-driven vector queries...exciting times.
I think systems that bet on existing databases eventually catching up (as is txtai's model) vs trying to reinvent the entire database stack will win out.