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

by zmccormick7 • 2 years ago

17 5 2 years 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

zmccormick72• 2 years 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• 2 years ago

Cool! What's next in the roadmap?

zmccormick72• 2 years 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• 2 years ago

extremely efficient: python.

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

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