If it's < 100M, with vectors of 1024 size, you could fit all of that in ~100G of memory. So, maybe storing it in memory is an easy way to go about it. This ignores a lot of "database problems".
If the docs are changing constantly, or uou have other scalability concerns, you may be better off using a "proper" vector db. There have been HN postings which indicate vector db choice matters. Do your research there.
Agreed. Pure in-memory is too risky for us given the persistence requirements and monthly updates. We are definitely going with a 'proper' DB (likely Postgres+pgvector or Weaviate) to handle the state and updates reliably.
