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
The number of people I know who’ve had unrecoverable shard failures on Qdrant is too high to take it seriously.
Works well for the vast majority of our customers (although we get the very occasional complaint about wanting a dev environment that works offline). The dataset sizes for local dev are usually so small that the cost rounds to free.
It's only occasional because the people who care about dev environments that work offline are most likely to just skip you and move on.
For actual developer experience, as well as a number of use cases like customers with security and privacy concerns, being able to host locally is essential.
Fair enough if you don't care about those segments of the market, but don't confuse a small number of people asking about it with a small number of people wanting it.
in many CI environments unit tests don't have network access, it's not purely a price consideration.
(not a turbopuffer customer but I have been looking at it)
Without that it’s unfortunately a non starter
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.
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.
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
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.)
I was curious given the cloud discussion - a quick search suggests default AWS SSD bandwidth is 250 MB/s, and you can pay more for 1 GB/s. Similar for s3, one http connection is < 100 MB/s, and you can pay for more parallel connections. So the hot binary quantized search index is doing a lot of work to minimize these both for the initial hot queries and pruning later fetches. Very cool!
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!
What CPU are they using here?
