Loading...
Vespa is an open-source serving engine with 6K+ GitHub stars for hybrid search combining vector similarity, BM25 text ranking, and structured filtering in a single query. Built by Yahoo for web-scale, it handles billions of documents with millisecond latency. Features real-time indexing, ML model serving, tensor computation, and ACID-compliant writes. Supports custom ranking models, query federation, and geographic search. Used for recommendation systems, personalization, and RAG.
Vespa combines vector, text, and structured search in one engine. Billions of documents, millisecond latency. Built by Yahoo for web-scale.
Real-time indexing, built-in ML model serving, tensor computation. ACID-compliant partial updates.
Custom ranking models, query federation, geographic search. Self-hosted or Vespa Cloud managed.
Free open-source / Vespa Cloud available
Self-hosted, Docker, Vespa Cloud
Embedded vector database for multimodal AI with petabyte scale
LanceDB is an open-source embedded vector database built on the Lance columnar format for multimodal AI. It delivers near in-memory performance from disk with zero-copy architecture, supporting vector search, full-text search, and SQL. Native SDKs for Python, TypeScript, and Rust integrate with LangChain, LlamaIndex, and DuckDB. Backed by a $30M Series A, used by Harvey AI and Runway, with 18,000+ GitHub stars.
Serverless vector and full-text search on object storage
turbopuffer is a serverless vector and full-text search engine built on object storage that delivers 10x lower costs than traditional vector databases. Used by Anthropic, Cursor, Notion, and Atlassian for production search workloads. Manages 2+ trillion vectors across 8+ petabytes with automatic scaling and no infrastructure management. Funded by Thrive Capital.
