GraphRAG-SDK and VeritasGraph
These are competitors offering different approaches to graph-based RAG systems—FalkorDB's SDK emphasizes scalability and performance with high adoption, while VeritasGraph targets enterprise security and on-premise deployment with verifiable attribution, so you would choose one based on whether your priority is speed/scale or governance/compliance.
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 VeritasGraph
bibinprathap/VeritasGraph
VeritasGraph: Enterprise-Grade Graph RAG for Secure, On-Premise AI with Verifiable Attribution
Combines hierarchical tree-based navigation with semantic knowledge graph reasoning to enable multi-hop retrieval and 100% verifiable attribution. Supports multiple deployment modes—lite with cloud APIs (OpenAI/Anthropic), local with Ollama (~8GB RAM), or full production with Neo4j—while including built-in vision RAG for extracting structured data from charts and tables. Integrates with optional UI (Gradio), Microsoft GraphRAG, and ingestion tools (YouTube/web articles).
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