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Vector DBFreemiumOpen Source
MARIADB
Enterprise relational database with native vector search support
GPL-2.0
ABOUT
Adding vector search to an existing application usually means introducing a separate vector database alongside the relational database, adding sync complexity and operational overhead. MariaDB solves this by embedding vector search directly into a battle-tested relational database — with VECTOR data type and vector indexes — so developers can run SQL queries with vector similarity in the same database that stores their application data.
INSTALL
docker run -p 3306:3306 mariadb:latestINTEGRATION GUIDE
1. Add semantic search to an existing MariaDB-backed application without introducing a separate vector database
2. Build a hybrid SQL-and-similarity query system for e-commerce that filters by category then ranks by vector similarity
3. Implement a recommendation engine that uses SQL for user demographics and vector search for product matching
4. Create a content management system with both structured metadata queries and embedding-based content discovery
5. Power a customer-facing search that combines relational filtering with vector-based relevance ranking
TAGS
sqlrelational-databasevector-searchmysql-compatiblehybrid-searchenterprisedocker