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GraphRAG

Microsoft
open source / Overall score: 3.4

Microsoft Research's graph-based RAG system. A model extracts entities and relationships from unstructured text into a knowledge graph, clusters it into hierarchical communities, generates community summaries, and answers through global, local and DRIFT search modes. It targets corpus-wide sensemaking questions that vector retrieval alone handles poorly.

Indexing is compute- and cost-intensive relative to a vector pipeline.

Openness

5 high confidence
5.0
license
MIT(OSI)
source
public
core features withheld
no

Fully MIT: the repo publishes the complete indexing and query pipeline and offers no hosted tier, enterprise directory or license key, so the core is ungated as well as OSI-licensed.

Adoption

2 high confidence
2.0

PyPI downloads are the basis for this reading, since graphrag is the package's declared distribution channel. GitHub stars on the same repository move in the same direction and corroborate the reading rather than driving it.

Capability

4 medium confidence
4.0

GraphRAG is turnkey for knowledge-graph-based retrieval: it extracts a graph, detects communities, generates summaries and supports Global, Local and DRIFT query modes with automatic prompt tuning. No benchmark exists for this kind of technique, so it is judged on feature depth, and it is deliberately narrower in scope than a general agent like OpenHands, placing it a step below.

  • https://microsoft.github.io/graphrag/ recorded 2026-09-29

    The docs describe "extracting a knowledge graph out of raw text, building a community hierarchy, generating summaries for these communities" and list Global Search, Local Search, DRIFT Search and Prompt Tuning.

Verified 2026-09-24