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Vector DBFreemiumOpen Source
CRATEDB
Distributed SQL database with vector search for real-time AI analytics
Apache-2.0
ABOUT
AI applications often need to combine vector similarity search with traditional SQL analytics, time-series data, and full-text search — requiring separate systems that increase complexity. CrateDB solves this by providing a single distributed SQL database that natively supports vector embeddings alongside relational tables, time-series data, and full-text search, all queryable through standard SQL.
INSTALL
docker run --publish=4200:4200 --publish=5432:5432 crate -Cnetwork.host=0.0.0.0INTEGRATION GUIDE
1. Build a real-time AI analytics dashboard combining vector similarity with SQL aggregations on streaming data
2. Create a hybrid search pipeline that blends semantic vector search with structured SQL filtering and sorting
3. Implement a time-series monitoring system with vector-based anomaly detection on IoT sensor data
4. Power a recommendation engine that uses SQL for business logic and vector search for semantic matching
5. Develop a log analytics platform that searches both log text and embedding vectors in a single query
TAGS
sqldistributedvector-searchtime-seriesfull-text-searchpostgresql-compatiblereal-timedocker