RAG vs GraphRAG: Choosing Retrieval Architectures

Choosing the right retrieval architecture directly impacts the accuracy and explainability of GenAI applications. The article compares standard Retrieval-Augmented Generation (RAG) with GraphRAG, highlighting how vector-based retrieval handles unstructured similarity, while graph-based approaches capture relationships, context, and multi-hop reasoning. It explains architectural trade-offs in data modeling, query complexity, and scalability. Technology leaders should align retrieval design with use case complexity, especially where context, traceability, and reasoning depth are critical.