It really depends on the setup that the dev/ops at customer are more comfortable with. Elastic or PostgreSQL can be both fine.
Personally for small cases (e.g. under 50k documents and 20GB of text) I like to use SQLite FTS, while linking text fragments to the additional metadata (native or extracted). This way I can really narrow down the search scope to a few case related documents in each conversation path.
But ultimately the flavor of DB and FTS is just an implementation detail. Most of them will do just fine.
Comments
Plus one for this approach, I’m trying to say broadly the same thing with my comment.
What are you using for full text search RAG in production?
It really depends on the setup that the dev/ops at customer are more comfortable with. Elastic or PostgreSQL can be both fine.
Personally for small cases (e.g. under 50k documents and 20GB of text) I like to use SQLite FTS, while linking text fragments to the additional metadata (native or extracted). This way I can really narrow down the search scope to a few case related documents in each conversation path.
But ultimately the flavor of DB and FTS is just an implementation detail. Most of them will do just fine.
Edit: fixed grammar.