I might be missing something but how is this different to amazon opensearch with ultrawarm storage? I think amazon launched this about 4 years ago right?
Marqo lets you use state of the art e5 embeddings (which are significantly more performant in retrieval than the openai embeddings), and will handle the embedding generation and retrieval on lucene indexes: https://www.marqo.ai/
marqo.ai has excellent indexing throughput as vector generation and vector retrieval are both contained within a marqo cluster. You can use it with multi-gpu, cpu, etc. It's also horizontally scalable.
Just to quickly add to ukuina's comment, marqo.ai does embedding generation and vector search end to end, so you can put in documents and the embeddings are automatically generated.
Marqo provides automatic, configurable chunking (for example with overlap) and can allow you to bring your own model or choose from a wide range of opensource models. I think e5-large would be a good one to try. https://github.com/marqo-ai/marqo
Someone from Marqo here - if you're looking for an end-to-end vector search DB that handles vector search and transformation you should check out marqo. https://github.com/marqo-ai/marqo
UKV looks really cool. At Marqo.ai we are achieving end-to-end semantic search building on top of existing embedding search functionality, keen to take a closer look at what you are doing. Seeing UKV come out on the cloud serverless will be super interesting - it's something thats taken us a while for us to work out.
This is really cool - would be awesome to connect at some point. I co-founded Marqo which also enables this through providing the semantic search component of this workflow. We've found some interesting results combining it with LLMs. https://www.marqo.ai/blog/from-iron-manual-to-ironman-augmen...