top | item 41599605

Show HN: MinDB – an extremely memory-efficient vector database

17 points| zmccormick7 | 1 year ago |github.com

5 comments

order

throwaway888abc|1 year ago

That's looks exciting. Do you guys have more detailed benchmarks (doesn't have to be polished article), pastebin welcome ?

Thank you, will keep an eye

zmccormick7|1 year ago

We've only done full benchmarking with the FIQA dataset, comparing minDB with Chroma. We're going to try it with Qdrant and Weaviate soon too, since they both have support for quantization, which will be a more apples-to-apples comparison with our approach.

We did test uploading and querying a Wikipedia dump, which was ~35M vectors. Query latency was around 150ms and peak memory usage was 1.5GB. We couldn't test recall, though, because we didn't have queries with ground truths.

pablomendes|1 year ago

Cool! What's next in the roadmap?

zmccormick7|1 year ago

The main thing we need to add is metadata filtering, as that's required for a lot of use cases. We're also thinking about adding hybrid search support and multi-factor ranking.

caeser|1 year ago

extremely efficient: python.