[EspadaV9]

If you need to store vector, surely the easiest solution is to run `CREATE EXTENSION vector`. When, or if, you need more, then look at alternatives, but I'm sure most people will have a much easier time just adding it to their existing database.

[canpan]

Pgvector is definitely the easiest way to get started. I did not really get the problem the article was trying to sell.

Setting up an ingestion pipeline to your existing db, vs ingesting into yet another db seems to not solve a problem I have.

If there was one thing I wish pgvector was better at, it would be to allow composite indexes (ie find vector where category). But it's a minor point.

[EspadaV9]

I was genuinely surprised just how easy it was to get a fully working RAG set up with Postgres. It was a few hours over a weekend to get something "working" and then probably a bit less time a following weekend to have a nicer database structure and rebuild it learning from the mistakes during the first attempt. The harder part comes next, because that involves multiple tables of user provided data, multi tenancy with a shared core vector schema, and all the actual business logic, so I've put it all on hold for a real breakdown now, but I wouldn't expect it to be much of a problem with what I've found so far with pgvector, and Postgres in general.

[kencho]

the article was aimed more at teams that don't have an existing postgres setup and are evaluating standalone vector databases from scratch. if you're already running postgres with pgvector, you're in a good spot