Show HN: A fast HNSW implementation in Rust

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • hnsw-rust

    HNSW implementation in Rust. Reference: https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf

  • Happy to see people working on vector search in Rust. Keep it up!

    As far as HNSW implementations go, this one appears to be almost entirely unfinished. Node insertion logic is missing (https://github.com/swapneel/hnsw-rust/blob/b8ef946bd76112250...) and so is the base layer beam search.

    OP, have you perhaps pushed an outdated branch?

  • hnswlib

    Header-only C++/python library for fast approximate nearest neighbors

  • How does this compare to hsnwlib - is it faster? https://github.com/nmslib/hnswlib

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • qdrant

    Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

  • Also compare with qdrant's Rust implementation; they tout their performance. https://github.com/qdrant/qdrant/tree/master/lib/segment/src...

  • tinyhnsw

    build your own vector database -- the littlest hnsw

  • I put together a slow (but readable!) HNSW implementation in python to really understand how it works: https://github.com/jbarrow/tinyhnsw

    Indexing time isn't great, but query time is surprisingly good for it being written in unoptimized python and numpy.

  • instant-distance

    Fast approximate nearest neighbor searching in Rust, based on HNSW index

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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