Beyond Text Search: When Relationship Graphs Beat Traditional RAG

While RAG's vector similarity approach works for simple lookups, it fails when questions depend on understanding relationships between entities. GraphRAG solves this by mapping connections across data, enabling AI systems to answer complex dependency-based queries that pure text retrieval cannot address. This shift is crucial for enterprise AI, where most real-world questions require understanding how data points connect rather than simply finding matching documents.