Weaviate
Cloud-native vector search engine
About
Open-source vector database with hybrid search (vector + BM25), multi-modal support, and native GraphQL API. Strong enterprise adoption.
Choose Weaviate when…
- •You want a knowledge graph alongside vector search
- •Multi-modal search (text + image) is needed
- •You need hybrid keyword + vector search
Builder Slot
The memory layer — stores and retrieves vector embeddings for RAG and semantic search
Other tools in this slot:
Stack Genome Detection
AIchitect's Genome scanner detects Weaviate in your project via these signals:
weaviate-clientweaviate-clientWEAVIATE_URLWEAVIATE_API_KEYIntegrates with (2)
LangChain wraps Weaviate's client in a vectorstore interface compatible with all LangChain retrievers.
→ Multimodal and multi-tenant semantic search within LangChain agents — Weaviate's object-level memory accessible from any chain.
LlamaIndex connects to Weaviate as a vector store, using its GraphQL API for multimodal and multi-tenant retrieval.
→ Multimodal RAG within LlamaIndex — retrieve across text, images, and structured data from a single Weaviate index.
Alternatives to consider (3)
Pricing
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