From Vector Search to Graph Reasoning: The Rise of Graph RAG

Vector search alone cannot capture relationships between entities that require multi-step reasoning. Graph RAG explicitly extracts entities and their relationships into a knowledge graph, enabling systems to answer complex questions spanning multiple documents through graph traversal. This hybrid approach—combining graph structure with vector fallback—represents a significant advancement in making RAG systems capable of sophisticated, multi-entity reasoning.