[TuringNYC]

>> I didn't quite follow your comment about vector support, are you asking for something beyond what pgvector + diskann provide (both available on Azure)?

You dont support ultra-wide vectors from the largest embeddings models. We have to wierd stuff like chop up vectors across fields.

[0xCMP]

Some thing I've learned, but rarely seen explained anywhere: Storing the vectors is most likely not an issue, mostly likely you're having a problem with the indexes on top of them in which case you can use quantized vector indexes[0] (handled by pgvector) which will get past the limits imposed by PostgreSQL.

I had to switch off pgvecto.rs at some point and figured that out.

I don't have specific experience with the Azure environment here, but this probably applies if you have access to pgvector.

[0]: Types of indexes + number of bits supported at bottom of this section: https://github.com/pgvector/pgvector#hnsw