Vector Databases & Semantic Search
32 repos
Vector databases and search systems designed to store, index, and query high-dimensional embeddings for semantic similarity matching. This cluster covers both specialized vector database engines (like Milvus, Qdrant, and Infinity) and hybrid search systems that combine vector search with traditional full-text indexing. Repositories span multiple language ecosystems—primarily Python clients and integrations, Rust and C++ for performance-critical database cores—reflecting the need for both accessible APIs and high-throughput backends. Projects here address the core infrastructure for AI-powered search, recommendation systems, and similarity-based retrieval.
Related clusters
mchl-labs/chronovec
Versioned vector index with MVCC, snapshot isolation, and branchable agent memory
