GraphRAG Review 2026

Microsoft's graph-based retrieval augmented generation for complex document understanding and multi-hop reasoning.

GraphRAG is Microsoft Research's open-source framework that enhances traditional RAG by building a knowledge graph from source documents before retrieval. Instead of simple vector similarity search, GraphRAG uses LLMs to extract entities and relationships from text, constructs a graph structure, detects communities using the Leiden algorithm, and generates summaries at multiple levels of abstraction.

The system operates in two modes: Local Search for specific questions that can be answered from nearby graph neighborhoods, and Global Search for holistic questions that require synthesizing information across the entire dataset. Global Search is GraphRAG's killer feature — it handles questions like 'What are the main themes in this dataset?' that traditional RAG completely fails at because no single chunk contains the answer.