A cloud-native vector database, storage for next generation AI applications
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Updated
Jun 13, 2024 - Go
A cloud-native vector database, storage for next generation AI applications
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.
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
An embedded vector database designed to run on edge devices. Lightweight and fast with HNSW indexing algorithm.
A specialized implementation of the Hierarchical Navigable Small World (HNSW) data structure adapted for efficient nearest neighbor lookup of approximate matching hashes
Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
The AI-native database built for LLM applications, providing incredibly fast full-text and vector search
MSVBASE is a system that efficiently supports complex queries of both approximate similarity search and relational operators. It integrates high-dimensional vector indices into PostgreSQL, a relational database to facilitate complex approximate similarity queries.
PostgreSQL vector database extension for building AI applications
Vector Database implemented in Golang with support for full-text and vector search as well as fault tolerance via Raft.
Fast and minimal header-only graph-based index for approximate nearest neighbor search (ANNS).
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
Fast approximate nearest neighbor searching in Rust, based on HNSW index
An R package for blocking records for record linkage / data deduplication based on approximate nearest neighbours algorithms.
A framework for the implementation of candidate generation/retrieval algorithms for recommender systems.
Rcpp bindings for the approximate nearest neighbors library hnswlib
What if an HNSW index was just a file, and you could serve it from a CDN, and search it directly in the browser?
Genkit AI framework plugin for HNSW vector database. save data into vector store for Retrieval Augmented Generation (RAG) implementation in Generative AI
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