Open SourceRAG15k
Weaviate
Vector DB with auto-embed modules and one-call hybrid search.
Weaviate is an open-source vector database that stores objects together with their vector embeddings and supports vector, keyword, and hybrid search. It includes optional modules for generating embeddings and for retrieval-augmented generation directly from the database, plus a GraphQL and REST/gRPC query interface. It is notable for its built-in vectorizer and generative modules that let it act as more than a bare vector store.
Repository
weaviate/weaviateLanguage
GoWhat you'd build with it
- Running hybrid (vector plus keyword) search over a knowledge base for higher-quality RAG retrieval
- Using built-in modules to vectorize and query content without managing a separate embedding pipeline
- Serving as a scalable, schema-aware vector backend for semantic search and recommendation features
Tags
vector-dbhybrid-searchgo