I have been looking into Postgres as a vector database option for some of the reasons you outlined in this blog. One thing I noticed when digging into pg_embedding specifically is "ef_search" controls the MAX number of neighbors you can return, which I don't think is the case for other hnsw indexes. Upping this value greatly increases the time of indexing (indexing with ef_search of 1000 took like 3-4 hours)
Does the Timescale vector index limit the number of results you can return? Does that impact speed of indexing or search? I wrote a blog about our somewhat niche requirements, which includes that we need to return ~10K or more results. If curious: https://medium.com/earthrisemedia/finding-a-vector-database-...
Interested in whether that would be a possibility with Timescale.
Does the Timescale vector index limit the number of results you can return? Does that impact speed of indexing or search? I wrote a blog about our somewhat niche requirements, which includes that we need to return ~10K or more results. If curious: https://medium.com/earthrisemedia/finding-a-vector-database-...
Interested in whether that would be a possibility with Timescale.