What is GraphRAG and When to Use It?

Standard RAG finds "similar" documents. GraphRAG finds "connected" concepts. Understanding when to use which is key to building a high-performance AI knowledge base.

Retrieval for Complex Relationships

Use GraphRAG when your data is highly interconnected. For example, if you are analyzing a series of legal cases or a complex codebase, a Knowledge Graph can track how different entities (people, files, laws) are related to each other. This allows the AI to perform "multi-hop" reasoning across your entire dataset.

Handling Global Queries

While standard RAG is great for specific questions ("What is the price of X?"), GraphRAG excels at global questions ("What are the recurring themes across all 500 documents?"). The graph provides a "bird's-eye view" of your knowledge, making it the superior choice for high-level research and discovery tasks.