A practical comparison of vector RAG and GraphRAG using a Neo4j movie dataset. Vector RAG finds semantically similar content via plot embeddings, while GraphRAG enriches those results by traversing graph relationships (genres, cast, ratings) before passing context to the LLM. A side-by-side terminal demo built with the neo4j-graphrag Python package illustrates how GraphRAG returns more accurate, structured answers — e.g., finding the highest-rated action film about other planets rather than just a plot-similar one. The demo connects to Neo4j's public dataset and requires only Python and an OpenAI API key.
Table of contents
What RAG and GraphRAG actually doThe recommendations datasetGet Martin Ohanlon’s stories in your inboxSeeing the differenceRun it yourselfLearn to build it yourselfNeo4j & GenerativeAI Fundamentals341 Impressions