GraphRAG-SDK and graphiti
These are complements—GraphRAG-SDK provides a framework for querying and reasoning over existing knowledge graphs, while Graphiti focuses on dynamically constructing and updating those knowledge graphs in real-time, so they address different stages of a graph-based RAG pipeline.
About GraphRAG-SDK
FalkorDB/GraphRAG-SDK
Build fast and accurate GenAI apps with GraphRAG SDK at scale.
Combines knowledge graphs, ontology extraction, and LLM inference via LiteLLM to enable GraphRAG workflows—automatically structuring unstructured data into queryable graphs stored in FalkorDB. Supports multi-vendor LLM deployment (OpenAI, Google, Azure, Ollama) and provides both ontology auto-detection from sources and chat-based query interfaces for knowledge graph traversal and augmented generation.
About graphiti
getzep/graphiti
Build Real-Time Knowledge Graphs for AI Agents
Provides temporal validity windows and provenance tracking for facts, enabling historical queries and full lineage from derived data to source episodes. Supports both prescribed (Pydantic-defined) and learned ontologies, with incremental graph updates that avoid costly recomputation. Integrates hybrid retrieval combining semantic embeddings, BM25 keyword search, and graph traversal for low-latency context assembly without LLM summarization.
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