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VSAG Documentation

VSAG is a high-performance, production-grade vector indexing library for similarity search. It powers vector retrieval in OceanBase and other projects at Ant Group, and is released under the Apache 2.0 license.

Features

  • Multiple index types: hnsw, hgraph, diskann, ivf, pyramid, sindi, brute_force, covering in-memory, memory-disk hybrid, sparse and multi-tenant scenarios.
  • Rich quantization: fp32 / fp16 / bf16 / int8 / sq8 / sq4 / pq, with SIMD dispatch on x86_64 and AArch64.
  • Advanced capabilities: range search, filtered search, serialization, conjugate graph enhancement, online Tune-based optimization, custom allocator / thread pool.
  • Language bindings: native C++, Python via pyvsag, Node.js / TypeScript via the npm package vsag.

How to Read This Documentation

  • User Guide — start here if you are new to VSAG: install, create an index, and run search.
  • Indexes — compare supported index types and look up their parameters.
  • Advanced Features — deep dives into specific search, serialization, memory, and hybrid-index capabilities.
  • Performance and Tuning — best practices, Tune, benchmarks, and evaluation tooling.
  • Developer Guide — building from source, running tests, and contributing.
  • Resources — release notes, roadmap, community links, related projects, papers, and contributors.

The Chinese version of the same documentation is available under docs/docs/zh/.