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Comparison

LightRAG vs graphrag

LightRAG (Simple and Fast Retrieval-Augmented Generation) vs graphrag (A modular graph-based Retrieval-Augmented Generation (RAG) system) - live GitHub stats and typed graph relationships, not marketing.

Markdown twin · LightRAG alternatives · graphrag alternatives

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LightRAG

HKUDS/LightRAG

★ 37kpushed Jul 8, 2026

graphrag

microsoft/graphrag

★ 34kpushed Jun 22, 2026

Tagline

LightRAG: Simple and Fast Retrieval-Augmented Generation
graphrag: A modular graph-based Retrieval-Augmented Generation (RAG) system

Stars

LightRAG: 37k
graphrag: 34k

Forks

LightRAG: 5.3k
graphrag: 3.6k

Open issues

LightRAG: 228
graphrag: 158

Language

LightRAG: Python
graphrag: Python

Adopt for

LightRAG: LightRAG is a Python library licensed under the MIT License, designed to offer efficient retrieval-augmented generation capabilities for enhancing large language model performance in genAI applications.
graphrag: GraphRAG offers a specialized graph-based approach to Retrieval-Augmented Generation (RAG) using the power of Large Language Models (LLMs) for enhancing unstructured data transformation and reasoning over private data.

Persona

LightRAG: -
graphrag: -

Runtime

LightRAG: -
graphrag: -

License

LightRAG: MIT
graphrag: MIT

Last pushed

LightRAG: Jul 8, 2026
graphrag: Jun 22, 2026

	LightRAG	graphrag
Tagline	Simple and Fast Retrieval-Augmented Generation	A modular graph-based Retrieval-Augmented Generation (RAG) system
Stars	37k	34k
Forks	5.3k	3.6k
Open issues	228	158
Language	Python	Python
Adopt for	LightRAG is a Python library licensed under the MIT License, designed to offer efficient retrieval-augmented generation capabilities for enhancing large language model performance in genAI applications.	GraphRAG offers a specialized graph-based approach to Retrieval-Augmented Generation (RAG) using the power of Large Language Models (LLMs) for enhancing unstructured data transformation and reasoning over private data.
Persona	-	-
Runtime	-	-
License	MIT	MIT
Last pushed	Jul 8, 2026	Jun 22, 2026
Categories	Data & Retrieval, LLM Frameworks	Data & Retrieval, Model Training
Trust and health
Maintenance	Very active (96%)	Active (82%)
Days since push	0d	16d
Open issues (now)	228	158
Full report	Trust report	Trust report
Typed relationship	LightRAG related graphrag

Choose LightRAG if…

Graph edge: LightRAG is a typed related of graphrag - see the relationship row above.
Tags unique to LightRAG: genai, large-language-models, retrieval-augmented-generation, knowledge-graph.
Also covers LLM Frameworks.
LightRAG ships Docker support for self-hosted deployment.
When you need quick integration of retrieval-augmented generation into your existing projects without complex setup. LightRAG is built for simplicity and speed which makes it ideal when rapid protypng

When NOT to use LightRAG

When you require highly complex and specialized configurations for your retrieval-augmented tasks, as LightRAG emphasizes simplicity over extensive customization.
In scenarios where strict control over every aspect of the retrieval process is necessary. Advanced customization options are limited compared to some competitors.
For projects with a small dataset or simple tasks that do not benefit significantly from RAG capabilities; LightRAG’s advantages may be underutilized.

GitHub Details

Choose graphrag if…

Graph edge: graphrag is a typed related of LightRAG - see the relationship row above.
Tags unique to graphrag: gpt-4, graph-based rag system.
Also covers Model Training.
- When you need to extract structured information from narrative or private data using LLMs and require a modular, graph-based system. - For projects that involve handling sensitive datasets where the

When NOT to use graphrag

- Avoid GraphRAG if your project requires minimal setup and cost since GraphRAG's indexing process can be resource-intensive.
- Not recommended for scenarios with extremely large datasets or when low latency is critical as this tool may pose significant computational demands.

GitHub Details

Explore

LightRAG trust report →graphrag trust report →Data & Retrieval category →LLM Frameworks category →Model Training category →All comparisons Stack workflows Trending tools

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Common questions

What is the difference between LightRAG and graphrag?: LightRAG: Simple and Fast Retrieval-Augmented Generation. graphrag: A modular graph-based Retrieval-Augmented Generation (RAG) system. See the comparison table for live GitHub stats and shared categories.
When should I choose LightRAG over graphrag?: Choose LightRAG over graphrag when Graph edge: LightRAG is a typed related of graphrag - see the relationship row above; Tags unique to LightRAG: genai, large-language-models, retrieval-augmented-generation, knowledge-graph; Also covers LLM Frameworks; LightRAG ships Docker support for self-hosted deployment; When you need quick integration of retrieval-augmented generation into your existing projects without complex setup. LightRAG is built for simplicity and speed which makes it ideal when rapid protypng.
When should I choose graphrag over LightRAG?: Choose graphrag over LightRAG when Graph edge: graphrag is a typed related of LightRAG - see the relationship row above; Tags unique to graphrag: gpt-4, graph-based rag system; Also covers Model Training; - When you need to extract structured information from narrative or private data using LLMs and require a modular, graph-based system. - For projects that involve handling sensitive datasets where the.
When should I avoid LightRAG?: When you require highly complex and specialized configurations for your retrieval-augmented tasks, as LightRAG emphasizes simplicity over extensive customization. In scenarios where strict control over every aspect of the retrieval process is necessary. Advanced customization options are limited compared to some competitors. For projects with a small dataset or simple tasks that do not benefit significantly from RAG capabilities; LightRAG’s advantages may be underutilized.
When should I avoid graphrag?: - Avoid GraphRAG if your project requires minimal setup and cost since GraphRAG's indexing process can be resource-intensive. - Not recommended for scenarios with extremely large datasets or when low latency is critical as this tool may pose significant computational demands.
Is LightRAG or graphrag more popular on GitHub?: LightRAG has more GitHub stars (37,451 vs 34,249). Stars measure visibility, not whether either tool fits your constraints.
Are LightRAG and graphrag open source?: Yes - both are open-source projects on GitHub (LightRAG: MIT, graphrag: MIT).
Where can I find alternatives to LightRAG or graphrag?: GraphCanon lists graph-backed alternatives at /tools/hkuds-lightrag/alternatives and /tools/microsoft-graphrag/alternatives (/tools/hkuds-lightrag/alternatives.md, /tools/microsoft-graphrag/alternatives.md), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?: Yes. The markdown twin at /compare/hkuds-lightrag-vs-microsoft-graphrag.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, LightRAG or graphrag?: LightRAG: Very active. graphrag: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for LightRAG and graphrag?: GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LightRAG: /tools/hkuds-lightrag/trust; graphrag: /tools/microsoft-graphrag/trust.