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Benchmarking Postgres Vector Search Approaches: Pgvector vs. Lantern
- systems 3y agoin summary it seems pgvector is faster where it counts
- binidxaba 3y agoLantern argues that being able to create indexes quickly is useful for tuning the hnsw paramters.
- chuckhend 3y agoReally great to see how the different config parameters (m, ef_construction, ef_search) impact latency and recall.
- darrenBaldwin03 3y agoInteresting blog! Makes me wonder what a comparison between Pinecone + ChromaDB + Pgvector would look like..
- nikita 3y agoDoes pgvector use parallel index build in this benchmark ?
- binidxaba 3y agoIt does not! Would be interesting to try that!
- dmezzetti 3y agoIf you'd like an alternate approach, txtai can store content in Postgres. This approach stores metadata/fields in the database and builds a Faiss/HNSW index alongside. The idea is to lean on two mature projects vs having to rewrite a full vector index implementation. https://neuml.hashnode.dev/external-database-integration https://neuml.hashnode.dev/external-database-integration https://github.com/neuml/txtai https://github.com/neuml/txtai Disclaimer: I'm the primary author of txtai