GraphRAG-SDK and nano-graphrag
These are competitors offering alternative implementations of GraphRAG architecture, with FalkorDB's SDK emphasizing production-scale performance and integration with its native graph database, while nano-graphrag prioritizes accessibility and hackability for development and experimentation.
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 nano-graphrag
gusye1234/nano-graphrag
A simple, easy-to-hack GraphRAG implementation
Builds knowledge graphs from text by extracting entities and relationships, then performs retrieval-augmented generation through both global and local graph traversal modes. Supports pluggable components including multiple LLM providers (OpenAI, Bedrock, Ollama), vector databases (FAISS, Milvus, HNSWlib), and graph backends (Neo4j, NetworkX), with full async/await support and MD5-based deduplication for incremental inserts.
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