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Post-co author here. This is actually something that we are considering implementing in future versions of pgai Vectorizer. You point the vectorizer at database A but tell it to cr…

Post co-author here. Really appreciate the feedback. Your point about HNSW being resource intensive is one we've heard. Our team actually built another extension called pgvectorsca…

Post co-author here. The point is a little nuanced, so let me explain: You are correct in saying that that you can store embeddings and source data together in many vectordbs. We a…

Good q. For most standalone vector search use cases, FAISS or a library like it is good. However, FAISS is not a database. It can store metadata alongside vectors, but it doesn't h…

Hey HN! Post co-author here, excited to share our new open-source PostgreSQL tool that re-imagines vector embeddings as database indexes. It's not literally an index but it functio…

While I value the depth in which the blog authors went into, some of these are not problems with pgvector but problems with similarity search itself and would be problems with othe…

There's actually quite a few ways to do shared database multi-tenant setups with pgvector. You can have separate out tenants into separate tables, schema, and even logical database…

See discussion for pgvectorscale in this HN post: https://news.ycombinator.com/item?id=40646276

Blog co-author here (PM at Timescale). We're excited to release pgvectorscale. Our team built this extension to make PostgreSQL a better database for AI and to challenge the notion…

Timescale recently released Timescale Vector [0] a scalable search index (DiskANN) and efficient time-based vector search, in addition to all capabilities of pgvector and vanilla P…

Agreed on pgvector being simple and a great choice for POCs and low scale, especially if you're familiar with Postgres. Our team released something new last week built for folks lo…

(Blog author here). Thanks for the question. In this case the index for both DiskANN and pgvector HNSW is small enough to fit in memory on the machine (8GB RAM), so there's no need…

Blog author here. This index is built in PostgreSQL. We make it very clear that this is cloud-only in the post and never mention OSS. While we offer it via the Timescale cloud plat…

Yup 2GB is fine (especially if using quantization), depending on the dataset size of course. Totally fair about cloud-only. Many developers prefer developing on cloud, but some pre…

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