A cloud-native vector database, storage for next generation AI applications
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Updated
Sep 5, 2024 - Go
A cloud-native vector database, storage for next generation AI applications
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
🛰️ An approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability.
PostgreSQL vector database extension for building AI applications
一款简单好用的 跨平台/多语言的 相似向量/相似词/相似句 高性能检索引擎。欢迎star & fork。Build together! Power another !
Visualize hnsw, faiss and other anns index
Graph-based Approximate Nearest Neighbor Search
Fast approximate nearest neighbor searching in Rust, based on HNSW index
Client Side Vector Database
⚡ A fast embedded library for approximate nearest neighbor search
Fast, SQL powered, in-process vector search for any language with an SQLite driver
CVT, a Computer Vision Toolkit.
(distributed) vector database
What if an HNSW index was just a file, and you could serve it from a CDN, and search it directly in the browser?
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