Production RAG: what I learned from processing 5M+ documents

Not here to schlep for AWS but S3 Vectors is hands down the SOTA here. That combined with a Bedrock Knowledge Base to handle Discovery/Rebalance tasks makes for the simplest implementation on the Market.

Once Bedrock KB backed by S3 Vectors is released from Beta it'll eat everybody's lunch.

Shill, not schlep.

I'm correcting you less out of pedantry, and more because I find the correct term to be funny.

I feel like I'm schelpin' through these comments, it's all mishigas

You feel like a schlemiel, perhaps?

more a schlimazel, Charles Schultzie, Lucy's everywhere

Especially now that if you google the word schlep, the first result is now something totally different than what you'd expect.

I think he just means it should be assumed to be standard practice and considered baseline at this point.

Assuming that's what he meant, why would it be considered baseline versus anything else? I am genuinely curious because I'd like to know more about issues people face with this or that vector store in general.

S3 Vectors is great in terms of cost. But it provides around 500ms median query latency for 1M vectors, unlike other vector stores. And it does not support keyword search and sparse vectors. So I think it is better to choose which vector store to use based on your requirements.