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DiskANN is a graph-based approximate nearest neighbor search (ANNS) system optimized for fast and accurate billion-point nearest neighbor search on a single node, leveraging SSD storage. It is highly relevant for large-scale vector database applications requiring efficient vector search at scale.
Hora is an efficient, open-source library for approximate nearest neighbor search, written in Rust. It offers high-performance vector search capabilities for AI and machine learning applications.
KDB is a high-performance vector database supporting billion-scale vector search, with features aimed at enterprises needing large-scale vector storage and retrieval.
NVIDIA CAGRA is a GPU-accelerated graph-based library for approximate nearest neighbor searches, optimized for high-performance vector search leveraging modern GPU parallelism. It is suitable for scenarios requiring rapid, large-scale vector retrieval.
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