Hi there. Another Convex cofounder here.

SiteGuide (https://siteguide.ai/) was the first to do vector embeddings with Convex, built by integrating Convex + Pinecone. This combination has been an increasingly common pattern over the last few months. So we put a template project to demonstrate how this is usually done:

https://github.com/ianmacartney/embeddings-in-convex

We're strongly considering building in vector search a little further down the road, but this is the recommended approach for now.

Convex cofounder here. Initial focus has been low-latency OLTP database workloads, which is pretty tied to the user-facing end-to-end reactivity angle we're pushing. As a bonus feature we also have built-in strongly consistent full text search, but not vector search.

So far our answer for folks who want alternative storage/query engines is to use our streaming Airbyte source connector or write directly to Pinecone, Snowflake, etc. This should work great for most devs.

There are likely always going to be some developers who want to use a particular third party database in addition to Convex, but we plan to expand built-in support for most workloads over time so that Convex is a truly full-stack backend replacement.