it's annoying to me that there's not a doc store with vectors. seems like the vector dbs just store the vectors I think.

> It also makes it easier for AWS to comply with censorship requirements.

Does it, how? Why would it be the vector store that would make it easier for them to censor the content? Why not censor the documents in S3 directly, or the entries in the relational database. What is different about censoring those vs a vector store?

This comment appears to misunderstand the control plane/data plane distinction of AWS. AWS does have limited access to your control plane, primarily for things like enabling your TAMs to analyze your costs or getting assistance from enterprise support teams. They absolutely do not have access to your dataplane unless you specifically grant it. The primary use case for the latter is allowing writes into your storage for things like ALB access logs to S3. If you were deep in a debug session with enterprise support they might request one-off access to something large in S3, but I would be surprised if that were to happen.

And what if they change their internal implementation and your code depends on the old architecture? It's good practice to clearly think about what to expose to users of your service.

The alternative is to find solutions that can reasonably support different requirements because business needs change all the time especially in the current state of our industry. From what I’ve seen, OSS Postgres/pgvector can adequately support a wide variety of requirements for millions to low tens of millions of vectors - low latencies, hybrid search, filtered search, ability to serve out of memory and disk, strong-consistency/transactional semantics with operational data. For further scaling/performance (1B+ vectors and even lower latencies), consider SOTA Postgres system like AlloyDB with AlloyDB ScaNN.

Full disclosure: I founded ScaNN in GCP databases and am the lead for AlloyDB Semantic Search. And all these opinions are my own.

> Things like this are why I'd much prefer if Amazon provided detailed documentation of how their stuff works, rather than leaving it to the development community to poke around and derive those details independently.

Absolutely this. So much engineering time has been wasted on reverse-engineering internal details of things in AWS that could be easily documented. I once spent a couple days empirically determining how exactly cross-AZ least-outstanding-requests load balancing worked with AWS's ALB because the docs didn't tell me. Reverse-engineering can be fun (or at least I kinda enjoy it) but it's not a good use of our time and is one of those shadow costs of using the Cloud.

It's not like there's some secret sauce here in most of these implementation details (there aren't that many ways to design a load balancer). If there was, I'd understand not telling us. This is probably less an Apple-style culture of secrecy and more laziness and a belief that important details have been abstracted away from us users because "The Cloud" when in fact, these details do really matter for performance and other design decisions we have to make.

That’s where my mind was rolling and also if not, can this be used in OpenSearch hybrid search?

I think you would be very surprised by the number of customers who don't care if the embeddings are SOTA. For every Joe who wants to talk GraphRAG + MTEB + CMTEB and adaptive rag there are 50 who just want whatever IT/prodsec has approved

Egress costs? I’m really surprised by this. Thanks for sharing.

Turbopuffer was mentioned in the article.

By the way, if you’re not fully satisfied with S3Vector’s write, query, or recall performance, I’d encourage you to take a look at what we’ve built with Zilliz Cloud. It may not always be the lowest-cost option, but it will definitely meet your expectations when it comes to latency and recall.

latency, actual retrieval performance, integrated pipelines that do more than just vector search to produce better results, the list goes on.

Postgres for vector search is fine for toy products or stuff that's outside the hot loop of your business but for high performance applications it's just inadequate.