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GraphRAG vs Vector RAG (EXPLAINED)

Scenario BasedRAGHard25 min read

Hard RAG interview question on graphrag vs vector rag — architecture, trade-offs, eval, and production patterns.

TL;DR — Quick Answer

Vector RAG retrieves similar text chunks via embeddings. GraphRAG extracts entities and relationships, builds community summaries, and supports global thematic questions plus multi-hop relational reasoning. Choose GraphRAG when queries need connected facts across many documents, not just local similarity.

The Interview Question

Explain graphrag vs vector rag. How would you design, implement, and evaluate this in a production RAG system? Discuss trade-offs and failure modes.

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