Traditional RAG benefits from simpler implementation/deployment, suits straightforward retrieval tasks, handles structured text data well, and has lower computational overhead, but loses structural information when chunking, can break related content, has limited ability to capture relationships, and struggles to reason across disparate facts—risking incomplete or fragmented answers.