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vsag

vsag is an Alibaba open-source library implementing efficient vector search algorithms, including approximate nearest neighbor search for high-dimensional vectors.

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About this tool

vsag

Brand: Alibaba
Category: SDKs & Libraries
Type: Open‑source vector indexing library

Overview

vsag is an open-source C++ vector indexing library for high-dimensional similarity search, designed to handle vector datasets that may not fit entirely in memory. It implements efficient vector search algorithms, including approximate nearest neighbor (ANN) search, and provides a Python wrapper package, pyvsag, for easier integration in Python environments.

Features

  • Vector similarity search

    • Supports high-dimensional similarity search and approximate nearest neighbor (ANN) queries.
    • Designed to work with vector sets of various sizes, including those that do not fit into memory.
  • Indexing algorithms

    • Implements the VSAG algorithm for efficient vector indexing and search.
    • Includes SINDI algorithm optimized for sparse vector search.
    • Provides example implementations such as HNSW-based indexing (e.g., 101_index_hnsw.cpp, example_hnsw.py).
  • Performance characteristics

    • SINDI algorithm for sparse vector search targets state-of-the-art performance, significantly improving QPS (queries per second) compared with prior solutions in internal tests.
    • Demonstrated efficiency on:
      • Sparse-full-inner-product tasks, with substantial QPS gains over previous SOTA and baseline algorithms on benchmark datasets.
      • gist-960-euclidean benchmarks, tested in the ann-benchmarks framework.
    • Benchmarks reported on multi-core CPU environments (e.g., Intel Xeon CPUs, AWS r6i.16xlarge), suitable for large-scale, CPU-based deployments.
  • Automatic parameter generation

    • Provides methods to generate algorithm parameters based on vector dimensions and data scale.
    • Aims to let developers use the library effectively without needing deep knowledge of the underlying algorithms.
  • Language support

    • C++ core implementation.
    • Python wrapper package: pyvsag available on PyPI.
  • Integration & build

    • CMake integration via FetchContent for easy inclusion in C++ projects.
    • Public C++ headers available via include directory.
    • Example CMake configuration for fetching and linking vsag in user projects.
    • Build-from-source instructions provided in a DEVELOPMENT.md guide in the repository.
  • Examples and usage

    • C++ and Python example programs provided in the examples directory.
    • Starter examples include:
      • 101_index_hnsw.cpp (C++)
      • example_hnsw.py (Python)
  • Ecosystem adoption

    • Used by multiple database and data systems, including (as listed in the repo):
      • OceanBase
      • TuGraph
      • GreptimeDB
      • Hologres
      • PolarDB

Tech Stack

  • Core language: C++ (C++11 standard or later)
  • Build system: CMake (3.11+ recommended)
  • Python wrapper: pyvsag (via PyPI)

Pricing

vsag is an open-source library. No pricing plans are listed; usage is free under the terms of its open-source license (see the GitHub repository for license details).

Links

  • Source code & documentation: https://github.com/alipay/vsag
  • Python package (pyvsag): https://pypi.org/project/pyvsag/
  • Benchmarks information: https://ann-benchmarks.com/ (external benchmark framework referenced by the project)
Surveys

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Information

Websitegithub.com
PublishedDec 25, 2025

Categories

1 Item
Sdks & Libraries

Tags

3 Items
#ANN
#high-dimensional
#vector search

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