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Maybe I’ve been using PostgreSQL too long but when faced with the choice of adding vector support to PostgreSQL or using a new technology, my first choice was to start with the PostgreSQL addition.

I’m not criticizing the specialized case for a true vector database, but for most workloads I agree that the big database players will be the right choice for many users.

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I'm in the same boat. For things that aren't huge scale, it's almost easier to find an extension or otherwise beat Postgres (or SQLite or Percona MySQL) into submission for your use case. Timescale is a really good example...I was really impressed how good the performance was for bigish (1 TB+) real time scientific time series data, even on a cheap Amazon Lightsail instance.

Pgvector's 2000-dimension limit on vector indices is annoying. There are workloads I want to push at it which are in the 5000+ range, so there's an extra dimensionality reduction step I need to build.

My starting point for pretty much any storage problem is "have you tried throwing it in postgresql" but this is one reason pulling something else off the shelf might be a good idea.

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