II.
KnowledgeFabricImpl overview
Reference · liveknowledge-fabric-impl:weaviate-fabric
Weaviate as Knowledge Fabric overview
Weaviate as a schema-aware knowledge fabric. Combines vector, keyword, and hybrid BM25+vector search with built-in vectorization modules for text, images, and multi-modal data. GraphQL and REST APIs provide flexible querying. Weaviate's generative search modules pipe retrieved context directly into LLM prompts, making it a native RAG backend. Multi-tenancy, filtering, and horizontal scaling support enterprise deployments. As a knowledge fabric, Weaviate uniquely combines structured schema awareness with semantic search.
Attributes
displayName
Weaviate as Knowledge Fabric
description
Weaviate as a schema-aware knowledge fabric. Combines vector, keyword, and
hybrid BM25+vector search with built-in vectorization modules for text,
images, and multi-modal data. GraphQL and REST APIs provide flexible
querying. Weaviate's generative search modules pipe retrieved context
directly into LLM prompts, making it a native RAG backend. Multi-tenancy,
filtering, and horizontal scaling support enterprise deployments. As a
knowledge fabric, Weaviate uniquely combines structured schema awareness
with semantic search.
knowledgeFileFormats
- embeddings
- document-chunks
- structured-objects
retrievalStrategy
hybrid
knowledgePersistence
vector-store
knowledgeScopes
- organization
- enterprise
autoExtractionSupport
false
notes
Weaviate's distinguishing feature as a knowledge fabric is its schema-aware
object model — knowledge is not just embedded vectors but typed objects with
properties and cross-references. This enables both semantic similarity search
and structured filtering. The built-in generative search module (generate)
makes it a complete RAG backend without external orchestration.
Outgoing edges
integrates_with1
- tool:weaviate·ToolWeaviate
realizes1
- layer:12-knowledge-fabric·LayerKnowledge Fabric
Incoming edges
None.