Weaviate Vector Database
A vector database that can combine embedding similarity, keyword relevance, and property filters.
Published by Weaviate
How to use it
Set up a collection with searchable text properties and choose whether to supply embeddings yourself or use a supported vectorizer. Keep a source URL or an internal document pointer on each object.
Compare keyword-only, vector-only, and hybrid results using the same judged queries. Adjust the hybrid weighting and check cases with exact names or error codes separately.
- Compatibility
- Docker, Python, REST, GraphQL
- Components
- Vector database, Keyword search, Hybrid retrieval
- Access
- Local server or managed service. Some vectorizer integrations require credentials.