Querying Knowledge Graphs with GraphRAG Toolkit | Amazon Web Services

AWS released the third post in its GraphRAG Toolkit series, now focusing on query-time graph search strategies.

The article compares pure vector retrieval with graph-based retrieval on a supply-chain example, showing where vector search misses relationship-heavy questions.

The toolkit starts with embedding-based top-k entry points, traverses the graph, and uses an LLM to generate either structured data or natural-language answers.

AWS positions GraphRAG as a way to improve retrieval accuracy for business decisions by combining vector search with knowledge-graph traversal.