How to compare Graph RAG tools
“Graph RAG” covers several architectures. Some extract a graph from documents, some query an existing property graph, and some enforce an operator-owned taxonomy. Select by graph source and evaluation needs—not by category label alone.
| Tool or approach | Graph source | Retrieval emphasis | Good fit | Primary evidence to demand |
|---|---|---|---|---|
| PrismRAG | User taxonomy, mapping rules, semantic edges, Louvain communities. | Community seed, BFS expansion, semantic re-ranking, direct fallback. | Category-safe retrieval in regulated or policy-owned domains. | Category bleed, recall@k, graph-path value, mapping trace, storage behavior. |
| Microsoft GraphRAG | Entities, relationships, claims, communities, and reports extracted from a corpus. | Local and global reasoning over graph artifacts and community summaries. | Corpus exploration and questions requiring relationship or theme synthesis. | Indexing cost, extraction quality, answer quality, prompt/model sensitivity. |
| Neo4j GraphRAG | An existing or constructed Neo4j property graph plus vector indexes. | Vector, graph traversal, Cypher, and hybrid retrieval patterns. | Teams already operating a property graph or requiring explicit graph queries. | Query correctness, graph coverage, traversal cost, schema maintenance. |
| LlamaIndex property graph | Property-graph construction and integrations configured in the LlamaIndex ecosystem. | Composable retrievers and query engines over graph and vector sources. | Applications already using LlamaIndex abstractions and connectors. | Extraction/retrieval quality, integration complexity, model and storage costs. |
Run one shared evaluation
Use the same corpus, access controls, questions, model/embedding budget, and hardware. Report recall@k, nDCG or MRR, answer support, category bleed, latency, indexing cost, update cost, and the percentage of results with a complete explanation. Separate graph benefit from the base semantic retriever.
PrismRAG scope
PrismRAG 0.2.1 is an Apache-2.0 Python library for taxonomy-controlled Graph RAG. Its public repository includes parity tests and a three-domain evaluation harness. The harness is not a neutral cross-vendor benchmark and publishes no comparative speed or accuracy claim.