Same 'knowledge graph + retrieval' label, three different bets: Microsoft GraphRAG v3.1.2 pays indexing cost for global summarization, LightRAG cuts cost with dual-level retrieval and incremental updates, HippoRAG 2 turns RAG into growing associative memory via PPR — this guide splits the trade-offs by component with four query modes, indexing pipelines, and a selection matrix.
CS224W is Stanford's machine learning with graphs course: nineteen lectures from node embeddings, GNNs, graph transformers and knowledge graphs to relational deep learning and GNNs with LLMs. The slides, three written homeworks and six Colabs are public and run as downloaded; the public recordings date from 2021, so the newer topics in the second half exist only as slides, and the exam and autograding are out of reach.
Vector search finds similarity; graph search traverses relationships. When a question requires reasoning across multiple entities — crag → route → sender → grade distribution — GraphRAG outperforms standard RAG.