The only production case I've seen of someone switching to a vector database totally in-lieu of a RDBMS is when their raw data lives in parquet / arrow files an

The only production case I've seen of someone switching to a vector database totally in-lieu of a RDBMS is when their raw data lives in parquet / arrow files and they need fast read-only searches in production. Then a periodic indexing daemon with some additional metadata bolted onto the vector definitions worked well and saved them from having to dip their toes into classic database optimization. Every place where I'm deploying vector databases, though, I'm using them as an alternative index just for searches (indexing embedding/id only) and doing the full object value lookup in the RDBMS. It's easier to optimize their vector clustering / sort performance outside the constraints of postgres - which is perhaps why pgvector suffers more under higher load.