As a principal eng, side-stepping a migration and having a good local dev experience is too good of a deal to pass up.

That being said, turbopuffer looks interesting. I will check it out. Hopefully their local dev experience is good

I really really enjoy & learn a lot from the mixedbread blog. And they find good stuff to open source (although the product itself is closed). https://www.mixedbread.com/blog

I feel like there's a lot of overlap but also probably a lot of distinction too. Pretty new to this space of products though.

Different vector indexes have very different recall and even different parameters for each dramatically impact this.

HNSW can have very good recall even at high vector counts.

There's also the embedding model, whether you're quantizing, if it's pure rag vs hybrid bm25 / static word embeddings vs graph connections, whether you're reranking etc etc

I'm not sure how that'd work with the binary quantization phase though. For example, we use Matroyska, and some of the bits matter way more than others, so that might be super painful.

When you're operating at the 100B scale, you're pushing beyond the capacity that most on-prem setups can handle. Most orgs have no choice but to put a 100B workload into the nearest public cloud. (For smaller workloads, considerations are different, for sure.)

turbopuffer will also continuously monitor production recall at the per-shard level (or on-demand with https://turbopuffer.com/docs/recall). Perhaps counterintuitively, the global recall will actually be better than the per-shard recall if each shard is asked for its own, local top_k!