Tool overview
Weaviate is listed under AI Infrastructure & MLOps AI tools.
What is Weaviate?
Weaviate is an open-source vector database that combines vector retrieval, keyword search, structured filtering, generative integrations, and multi-tenancy. It runs locally or self-hosted and is also available through managed Weaviate Cloud.
Best for
Teams building scalable semantic search, RAG, recommendations, and agent-memory systems
Who is it for?
Decision note
Rebuilt from the original export under V412/V411 independent factual verification. Preview only; Apply requires Failures = 0, Warnings = 0, Unmapped = 0, Missing = 0, reviewed explicit clears, image import disabled or V380 PASS, representative edit-screen comparison, and a zero-change post-Apply Preview.
Key features
Vector, keyword, and hybrid search
Structured filtering and multi-tenancy
REST, GraphQL, gRPC, and client APIs
Managed cloud and self-hosted deployment
Use cases
Build retrieval-augmented generation
Create semantic search applications
Power recommendations and similarity matching
Store memory and context for AI agents
Pros
- BSD-3-Clause open-source core
- Free cloud sandbox and local deployment
- Large integration and partner ecosystem
Limitations
The free sandbox is intended for experimentation and does not include paid support or production SLAs.
Vector quality depends on embedding choices, schema design, filters, and indexing configuration.
Pricing details
Billing options
Pricing note
The open-source database and Weaviate Cloud Sandbox are free. Production Flex clusters are billed by resource usage and support level; Plus and Premium add commitments, security, and stronger SLAs.
Supported languages
- English
Integrations
Embedding providers
Generative model providers
Kubernetes
Cloud marketplaces
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