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PatANN is a massively parallel, distributed, and scalable in-memory/on-disk vector database library for efficient nearest neighbor search across large-scale datasets by finding vector patterns.

Project description

PatANN - Pattern-Aware Vector Database / ANN

Overview

PatANN is a massively parallel, distributed, and scalable vector database library for efficient nearest neighbor search across large-scale datasets by finding vector patterns.

Status

Beta Version: Currently uploaded for benchmarking purposes. Complete documentation and updates are under development. Not for production use yet.

Platforms

  • Beta Version: Restricted to Linux to prevent premature circulation of beta versions
  • Production Releases (late April 2025)*: Will support all platforms that are supported by mesibo

Key Features

  • Faster Index building and Searching
  • Supports both in-memory and on-disk operations
  • Dynamic sharding to load balance across servers
  • Refined search, filtering and pagination
  • Unlimited scalability without pre-specified capacity

Algorithmic Approach

  • Novel pattern-based probing technique for ANN search
  • Preliminary results show phenomenal performance in building index and searching
  • Potential slight variations in lower-end matching
  • Detailed research paper forthcoming

Contributions

We are seeking help to:

  • Run additional datasets. So far, all tested datasets (including self-generated) exhibit patterns that helps algorithm. We have yet to test datasets without clear patterns or with uniform distribution.
  • Validate and improve the algorithm

Contact

For support / questions, please contact: support@mesibo.com

Project details


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