4 ms·
Congratulations, can anyone give an insight on how this compares to pg_embedding [0] (Postgres and use HNSW). Or the use-cases compared to other victor database
by thawab 3y ago
Congratulations, can anyone give an insight on how this compares to pg_embedding [0] (Postgres and use HNSW). Or the use-cases compared to other victor databases.
It’s getting hard to keep up what’s happening in the LLM scene.
[0] https://github.com/neondatabase/pg_embedding https://github.com/neondatabase/pg_embedding
- kordlessagain 3y agoI suspect a lot of the paying use cases for vector search right now have a lot to do with enterprise search functionality. As for the LLM stuff, I do wonder if it's paying bills yet. If anyone is into embeddings, check out Instructor Large/XL. It's quite good and super fast using L4s. Haven't quite figured out the instructions bits yet, but got it clustering things today and that was cool.
- roseway4 3y agoJonathan did just that in his prior blog post: https://jkatz05.com/post/postgres/pgvector-hnsw-performance/ https://jkatz05.com/post/postgres/pgvector-hnsw-performance/ pgvector_hnsw outperforms pg_embedding using a query per sec / recall measure across various common embedding widths and a range of dataset sizes.