HNSW (Rust)
A Rust implementation of the HNSW (Hierarchical Navigable Small World) approximate nearest neighbor search algorithm, useful for building high-performance, memory-safe vector search components in Rust-based AI and retrieval systems.
About this tool
HNSW (Rust)
Category: SDKs & Libraries
Brand: rust-cv
Website/Source: https://github.com/rust-cv/hnsw
License: MIT
Slug: hnsw-rust
Description
A Rust implementation of the Hierarchical Navigable Small World (HNSW) approximate nearest neighbor (ANN) search algorithm, designed for fast, memory-safe vector search in Rust-based AI, retrieval, and search systems.
Features
- Hierarchical Navigable Small World (HNSW) graph implementation for efficient approximate nearest neighbor search.
- Fast ANN search optimized for high-performance vector similarity queries.
- Rust-native library leveraging Rust’s safety and performance guarantees.
serdeintegration (optional feature flag): enable theserdefeature to serialize and deserialize HNSW data structures.- Examples and benches included in the repository (
examples,benchesfolders) to demonstrate usage patterns and performance. - Tests and implementation notes (
tests,implementation.md) documenting and validating the algorithm behavior. - No-std compatibility checks via
ensure_no_stddirectory, indicating attention to usage in constrained environments (where applicable).
Pricing
- Open-source under the MIT License (no usage fee).
Loading more......
Information
Categories
Tags
Similar Products
6 result(s)A Go implementation of the HNSW approximate nearest neighbor search algorithm, enabling developers to embed efficient vector similarity search directly into Go services and custom vector database solutions.
jvector is a high-performance Java-based library and engine for vector search and approximate nearest neighbor indexing.
NearestNeighbors.jl is a Julia package implementing various nearest neighbor search algorithms and index structures for high-dimensional vector data.
Voyager is a Spotify open-source vector search library and service for efficient nearest neighbor search on large-scale vector datasets.
vsag is an Alibaba open-source library implementing efficient vector search algorithms, including approximate nearest neighbor search for high-dimensional vectors.
NVIDIA CAGRA is a GPU-accelerated graph-based library for approximate nearest neighbor searches, optimized for high-performance vector search leveraging modern GPU parallelism. It is suitable for scenarios requiring rapid, large-scale vector retrieval.