Now that opensearch has ivfpq, and I assume pgvector will get it within 6mo... the current typical case for most teams, big or small, should be handled. Regular

Now that opensearch has ivfpq, and I assume pgvector will get it within 6mo... the current typical case for most teams, big or small, should be handled. Regular databases are all adding it, further chiseling away at the need for dedicated vector DB startups. This seems consistent with what we guessed would happen at the bottom of https://gradientflow.com/the-vector-database-index/ https://gradientflow.com/the-vector-database-index/ . AFAICT standalone optimized vector stores will still have their place, like super latency sensitive or high-throughput scenarios. Unfortunately for many stakeholders, venture-scale returns to justify the megarounds from the peak vc fomo of the last few years seems unclear. The TBD hail mary here may be generative AI: even if most modern vector search workloads are largely fine with regular DB extensions to support a few kinds of vector indexes, the continued growth of generative AI, knowledge graphs, etc., may somehow grow the pie for non-standard DBs here. That's not obvious to me. For example, with Databricks LakehouseIQ, a lot of the use case may be eaten by the data warehouses.