DiskANN is a suite of scalable, accurate and cost-effective approximate nearest neighbor search algorithms for large-scale vector search that support real-time changes and simple filters. This code is based on ideas from Microsoft's DiskANN. The main branch now contains a rearchitected project written in Rust.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

See guidelines for contributing to this project.

Older C++ code is retained on the cpp_main branch, but is not actively developed or maintained. The legacy C++ code was forked off from code for NSG algorithm.

If you use the C++ version in your software please cite the following:

@misc{diskann-github,
   author = {Simhadri, Harsha Vardhan and Krishnaswamy, Ravishankar and Srinivasa, Gopal and Subramanya, Suhas Jayaram and Antonijevic, Andrija and Pryce, Dax and Kaczynski, David and Williams, Shane and Gollapudi, Siddarth and Sivashankar, Varun and Karia, Neel and Singh, Aditi and Jaiswal, Shikhar and Mahapatro, Neelam and Adams, Philip and Tower, Bryan and Patel, Yash}},
   title = {{DiskANN: Graph-structured Indices for Scalable, Fast, Fresh and Filtered Approximate Nearest Neighbor Search}},
   url = {https://github.com/Microsoft/DiskANN},
   version = {0.6.1},
   year = {2023}
}