HomeToolsMCPHow It WorksStoriesPhilosophyArchitectureStar on GitHub
All Tools
V
Vector DBFreemiumOpen Source

VESPA

Open-source engine for real-time vector, text, and structured search

Apache-2.0

ABOUT

Teams building retrieval systems often need vector similarity, keyword search, metadata filters, and ranking over large datasets that change continuously. Vespa combines vector search, text search, tensor operations, filtering, and learned ranking in one engine so developers can serve low-latency retrieval and recommendation workloads without stitching together separate serving layers.

INSTALL
docker run --detach --name vespa --hostname vespa-tutorial --publish 8080:8080 --publish 19071:19071 --publish 19092:19092 vespaengine/vespa

INTEGRATION GUIDE

1. Build hybrid search across text, vectors, and metadata filters 2. Power RAG retrieval with ranking, filtering, and real-time index updates 3. Serve recommendation and personalization systems for content or products 4. Run large-scale semantic search over enterprise or application data

TAGS

vector-databasesearchhybrid-searchretrievalrankingannopen-source