# LightRAG vs RAGFlow

**Leader by vioscaleAI score:** LightRAG

| Attribute | LightRAG | RAGFlow |
|---|---|---|
| **vioscaleAI score** | 61.7 (53% (medium)) | 53.5 (9% (low)) |
| activity.commits_last_30d | 100 | - |
| adoption.dependent_repos | 0 | - |
| adoption.github_stars | 40,136 | - |
| content.faq | `[{"answer":"A lightweight RAG system that processes documents through flexible parsing engines and supports local deployment of embedding, reranking, and storage backends. Includes built-in citation attribution and can work with various open-source LLMs and embedding models. It is indexed under RAG Tools.","source":"https://github.com/pricing","question":"What is LightRAG?","confidence":0.6},{"answer":"LightRAG supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://github.com/pricing","question":"What platforms does LightRAG support?","confidence":0.6},{"answer":"Yes. LightRAG can be deployed cloud / SaaS, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://github.com/pricing","question":"Can LightRAG be self-hosted?","confidence":0.6},{"answer":"Yes. LightRAG is published under the MIT licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.","source":"https://github.com/HKUDS/LightRAG","question":"Is LightRAG open source?","confidence":0.95}]` | `[{"answer":"An AI platform that combines retrieval-augmented generation with autonomous agent features, enabling developers to create production-ready AI systems from complex data sources. It supports multiple deployment models (cloud or self-hosted Docker), integrates with various LLM providers and data sources, and provides streamlined workflows for enterprises of any scale. It is indexed under RAG Tools.","source":"https://ragflow.io","question":"What is RAGFlow?","confidence":0.6},{"answer":"RAGFlow is open source, so it can be self-hosted and used at no licence cost. Pricing changes often, so verify at source before relying on it.","source":"https://ragflow.io","question":"Is RAGFlow free to use?","confidence":0.6},{"answer":"RAGFlow supports the web, Windows, macOS, Linux and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://ragflow.io","question":"What platforms does RAGFlow support?","confidence":0.6},{"answer":"Yes. RAGFlow can be deployed cloud / SaaS and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://ragflow.io","question":"Can RAGFlow be self-hosted?","confidence":0.6},{"answer":"We have confirmed 13 integrations for RAGFlow, including Discord, Feishu, Telegram, Line, Confluence, S3, Notion and Google Drive, plus 5 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://ragflow.io","question":"What does RAGFlow integrate with?","confidence":0.6}]` |
| deployment.options | `{"on_prem":true,"self_hosted":true}` | `{"cloud":true,"self_hosted":true}` |
| description.long | An open-source RAG system designed for high scalability that uses both knowledge graphs and vector search to retrieve information from large datasets with reduced computational overhead and faster response times. | RAGFlow is an open-source RAG engine that streamlines data processing and integration for building production-ready AI systems. It supports multiple data formats and provides configurable LLM and embedding options with agent-based workflows. |
| features.capabilities | `{"open_source":true,"multimodal_rag":true,"hybrid_retrieval":true,"citation_attribution":true,"llm_provider_agnostic":true,"reranking_integration":true,"managed_ingestion_pipeline":true,"embedding_provider_agnostic":true,"multi_hop_agentic_retrieval":false}` | `{"open_source":true,"multimodal_rag":true,"citation_attribution":true,"llm_provider_agnostic":true,"managed_ingestion_pipeline":true,"embedding_provider_agnostic":true,"multi_hop_agentic_retrieval":true}` |
| integrations.count | 9 | 12 |
| integrations.list | `[{"name":"PostgreSQL","native":true,"category":"storage"},{"name":"Neo4j","native":true,"category":"storage"},{"name":"MongoDB","native":true,"category":"storage"},{"name":"Milvus","native":true,"category":"storage"},{"name":"Qdrant","native":true,"category":"storage"},{"name":"Redis","native":true,"category":"storage"},{"name":"Memgraph","native":true,"category":"storage"},{"name":"MinerU","native":true},{"name":"Docling","native":true}]` | `[{"name":"Discord"},{"name":"Feishu"},{"name":"Telegram"},{"name":"Line"},{"name":"Confluence"},{"name":"S3"},{"name":"Notion"},{"name":"Google Drive"},{"name":"OpenAI"},{"name":"DeepSeek"},{"name":"Gemini"},{"name":"OpenClaw"},{"name":"OpenAI GPT-5","native":true,"category":"llm"},{"name":"Google Gemini 3 Pro","native":true,"category":"llm"},{"name":"DeepSeek v4","native":true,"category":"llm"},{"name":"MCP","native":true}]` |
| language.primary | Python | - |
| license.spdx | MIT | - |
| platform.support | `{"cli":true,"mac":true,"web":true,"linux":true}` | `{"web":true,"linux":true}` |
| pricing | `{"type":"open_source","sourceUrl":"https://github.com/pricing","retrievedAt":"2026-09-14T09:25:31.588Z"}` | `{"type":"open_source","freeTier":true,"sourceUrl":"https://ragflow.io","retrievedAt":"2026-09-05T21:04:46.611Z"}` |
| pricing.free_tier | - | yes |
| pricing.model | open_source | open_source |
| pricing.price_level | free | free |
| pricing.transparent | - | yes |
| release.cadence_days | 7 | - |
| release.history | `[{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.7","date":"2026-09-02T07:23:55Z","type":"stable","version":"v1.5.7"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.7rc2","date":"2026-08-19T07:01:48Z","type":"stable","version":"v1.5.7rc2"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.7rc1","date":"2026-08-17T06:47:01Z","type":"prerelease","version":"v1.5.7rc1"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.6","date":"2026-08-06T08:29:47Z","type":"stable","version":"v1.5.6"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.5","date":"2026-07-31T12:07:29Z","type":"stable","version":"v1.5.5"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.5rc1","date":"2026-07-13T19:33:37Z","type":"prerelease","version":"v1.5.5rc1"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.4","date":"2026-06-24T10:24:01Z","type":"stable","version":"v1.5.4"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.3","date":"2026-06-14T06:21:33Z","type":"stable","version":"v1.5.3"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.2","date":"2026-06-11T06:14:51Z","type":"stable","version":"v1.5.2"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.1","date":"2026-06-09T08:32:30Z","type":"stable","version":"v1.5.1"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.0","date":"2026-06-03T01:54:09Z","type":"stable","version":"v1.5.0"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.5.0rc3","date":"2026-05-26T09:27:02Z","type":"prerelease","version":"v1.5.0rc3"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.16","date":"2026-05-07T19:34:01Z","type":"stable","version":"v1.4.16"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.15","date":"2026-04-19T08:40:25Z","type":"stable","version":"v1.4.15"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.14","date":"2026-04-12T20:43:18Z","type":"stable","version":"v1.4.14"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.13","date":"2026-04-02T17:00:24Z","type":"stable","version":"v1.4.13"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.12","date":"2026-03-27T05:52:31Z","type":"stable","version":"v1.4.12"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.11","date":"2026-03-20T08:41:06Z","type":"stable","version":"v1.4.11"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.11rc2","date":"2026-03-13T06:19:07Z","type":"stable","version":"v1.4.11rc2"},{"url":"https://github.com/HKUDS/LightRAG/releases/tag/v1.4.10","date":"2026-02-27T07:39:59Z","type":"stable","version":"v1.4.10"}]` | - |
| security.disclosure_policy | yes | - |
| security.trust_center | https://github.com/HKUDS/LightRAG/security | - |
| security.vulnerabilities | `{"count":10,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=lightrag-hku&per_page=100","last_12m":9,"max_severity":"CRITICAL"}` | - |

## Capabilities (RAG Tools)

| Capability | LightRAG | RAGFlow |
|---|:--:|:--:|
| **Capabilities** |  |  |
| Hybrid retrieval | ✓ | - |
| Reranking integration | ✓ | - |
| Multi hop agentic retrieval | ✗ | ✓ |
| Embedding provider agnostic | ✓ | ✓ |
| LLM provider agnostic | ✓ | ✓ |
| Built in rag eval metrics | - | - |
| Citation attribution | ✓ | ✓ |
| Multimodal rag | ✓ | ✓ |
| Managed ingestion pipeline | ✓ | ✓ |
| Open source | ✓ | ✓ |

*Source: vioscaleAI. Generated 2026-10-16T02:35:17.099Z. "-" = undocumented, not absent.*