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Comment by ricw | Hacker News Reader

I’ve been using this since early this year and it’s been great. It was what convinced me to just stick to Postgres rather than using a dedicated vector db.

Only working with 100m or so vectors, but for that it does the job.

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Are you using a dedicated pg instance for vector or you keep all your data in a single pg instance (vector and non-vector)?

The biggest selling point to using Postgres over qdrant or whatever is that you can put all the data in the same db and use joins and ctes, foreign keys and other constraints, lower latency, get rid of effectively n+1 cases, and ensure data integrity.

I generally agree that one database instance is ideal, but there are other reasons why Postgres everywhere is advantageous, even across multiple instances:

- Expertise: it's just SQL for the most part - Ecosystem: same ORM, same connection pooler - Portability: all major clouds have managed Postgres

I'd gladly take multiple Postgres instances even if I lose cross-database joins.

Yep. If performance becomes a concern, but we still want to exploit joins etc, it's easy to set up replicas and "shard" read only use cases across replicas.

Postgres supports the Foreign Data Wrapper concept from SQL/MED. If you configure this you can do joins across instances, even!

https://www.postgresql.org/docs/current/postgres-fdw.html

All in one of course. That’s the biggest advantage. And why postgres is great - it covers virtually all standard use cases.

What kind of performance do you observe with what setup?

Depends on the query and I don’t have exact numbers of the top of my head, but we’re talking low 100ms range for something pgvector itself wasn’t able to handle in a reasonable amount of time.

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