HNSWLIB
HNSWLIB is a C++ library with Python bindings for fast approximate nearest neighbor search using Hierarchical Navigable Small World (HNSW) graphs, commonly used in vector database backends.
About this tool
HNSWLIB
HNSWLIB is a header-only C++ library with Python bindings for fast approximate nearest neighbor (ANN) search using Hierarchical Navigable Small World (HNSW) graphs.
Features
- Fast Approximate Nearest Neighbor Search: Implements the HNSW algorithm for efficient high-dimensional vector search.
- Header-only C++ Implementation: No dependencies other than C++11.
- Python Bindings: Full support for Python with picklable index objects.
- Incremental Index Construction: Supports adding, updating, and deleting elements from the index.
- Multi-threading Support: Multi-threaded index construction and search; configurable number of threads.
- Custom Distances: C++ interface allows user-defined distance functions.
- Supported Distance Metrics:
- Squared L2 ('l2')
- Inner Product ('ip')
- Cosine Similarity ('cosine')
- Filtering Support: Ability to filter search results by element labels.
- Efficient Memory Usage: Lower memory footprint and faster build time compared to some alternatives.
- Serialization/Deserialization: Save/load indexes to/from disk; supports pickle in Python.
- Replace Deleted Elements: Option to reuse memory of deleted elements.
- Index Resizing: Dynamically increase/shrink the index capacity.
- Multi-vector Document Search and Epsilon Search: Available in C++ interface.
- Java and R Support: External bindings available.
- Cross-platform: Usable in C++ and Python environments; external implementations for other languages (Go, Julia, Rust, Java, .NET, etc.).
Usage Highlights
- Create, initialize, and manage ANN indexes in both C++ and Python.
- Insert, update, delete, and query vectors.
- Batch operations for both insertions and queries.
- Save/load indexes for persistence and scaling.
- Fine-tune speed/accuracy trade-offs with parameters like
efandM.
Installation
- Install via pip:
pip install hnswlib - Or build from source (see GitHub for details).
License
- Apache-2.0
Pricing
- Open Source: Free to use under the Apache-2.0 license.
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