VexDB-Lite is a vector similarity search library providing Approximate Nearest Neighbor (ANN) capabilities as extensions for PostgreSQL, DuckDB, and SQLite databases. The system implements Hierarchical Navigable Small World (HNSW) graphs for efficient similarity search, with optional Product Quantization and RaBitQ compression for memory efficiency. It features hardware-accelerated distance computation using SIMD instructions (SSE, AVX, AVX512, NEON) and provides multiple distance metrics (L2, inner product, cosine). The architecture separates core algorithms from database-specific adapters, enabling consistent functionality across different storage engines. The codebase demonstrates strong engineering practices with reusable components like the SIMD dispatch system, vector buffer manager, and product quantization implementation.
EFANNA is a header-only C++ library for approximate nearest neighbor (ANN) search. It builds an index combining a k-nearest neighbors graph and tree structures (KD-trees or hash tables) to enable efficient search on high-dimensional data. The library provides optimized distance computations with SSE/AVX intrinsics and a matrix class for SIMD-friendly data access. Key functionalities include index building, saving/loading indices, and performing ANN search via command-line examples or a MATLAB interface. The architecture is modular, with core algorithms in base_index.hpp and specialized index implementations in kdtreeub_index.hpp and hashing_index.hpp.