--- title: "ragflow vs UFO" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/infiniflow-ragflow-vs-microsoft-ufo" tools: ["infiniflow-ragflow", "microsoft-ufo"] --- # ragflow vs UFO Neutral, constraint-first comparison with live GitHub stats. | | [ragflow](/tools/infiniflow-ragflow.md) | [UFO](/tools/microsoft-ufo.md) | | --- | --- | --- | | Tagline | Retrieval-Augmented Generation (RAG) engine fusing Agent capabilities with LLM context management | Weaving the Digital Agent Galaxy | | Stars | 84,561 | 9,270 | | Forks | 9,862 | 1,038 | | Open issues | 2,325 | 75 | | Language | Go | Python | | Adopt for | Decide whether to use RAGFlow based on its unique integration of retrieval and AI agent capabilities for generating enhanced context layers with LLMs, while considering its language choice (Go) and Apache-2.0 license. | UFO³ is a cutting-edge tool designed for cross-device collaboration and task orchestration through Directed Acyclic Graphs (DAG). It stands out with its capabilities in asynchronous execution, dynamic DAG editing, and a統 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Data & Retrieval | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ragflow](/tools/infiniflow-ragflow.md) | [UFO](/tools/microsoft-ufo.md) | | --- | --- | --- | | Open issues (now) | 2.3k | 75 | | Security scan | 4 low (4 low) | 28 low (28 low) | | Full report | [trust report](/tools/infiniflow-ragflow/trust.md) | [trust report](/tools/microsoft-ufo/trust.md) | **Typed relationship:** ragflow _(alternative)_ UFO RAGFlow focuses on Retrieval-Augmented Generation and LLM context management, similar to UFO³'s task focus areas including complex automation and task orchestration. ## Decision facts: ragflow - **Pricing:** freemium - RAGFlow is offered under an Apache-2.0 license, making the core functionality free and open-source. However, there may be additional costs associated with hosting, infrastructure maintenance, and any云 - **Adopt for:** Decide whether to use RAGFlow based on its unique integration of retrieval and AI agent capabilities for generating enhanced context layers with LLMs, while considering its language choice (Go) and Apache-2.0 license. ## Decision facts: UFO - **Adopt for:** UFO³ is a cutting-edge tool designed for cross-device collaboration and task orchestration through Directed Acyclic Graphs (DAG). It stands out with its capabilities in asynchronous execution, dynamic DAG editing, and a統 ## Choose when ### Choose ragflow if… - ragflow is primarily Go; UFO is Python. - License: ragflow is Apache-2.0, UFO is MIT. - Pricing: RAGFlow is offered under an Apache-2.0 license, making the core functionality free and open-source. However, there may be additional costs associated with hosting, infrastructure maintenance, and any云. - RAGFlow focuses on Retrieval-Augmented Generation and LLM context management, similar to UFO³'s task focus areas including complex automation and task orchestration. - Tags unique to ragflow: context-management, llm-context-layer, rag, agentic-ai. - Also covers Data & Retrieval. - ragflow ships Docker support for self-hosted deployment. - When you need a tool that integrates both retrieval-augmented generation and AI agent functionalities to enhance the contextual layer for any use case involving large language models. ### Choose UFO if… - UFO is primarily Python; ragflow is Go. - License: UFO is MIT, ragflow is Apache-2.0. - RAGFlow focuses on Retrieval-Augmented Generation and LLM context management, similar to UFO³'s task focus areas including complex automation and task orchestration. - Tags unique to UFO: windows, llm, gui, copilot. - Also covers Developer Tools. - - You need to manage complex multi-step automation workflows across multiple devices. ## When NOT to use ragflow - If your project strictly requires a Python environment as RAGFlow is written in Go, transitioning or integrating might pose technical challenges. - In situations where you need real-time processing capabilities superior to what's currently offered by RAGFlow’s architecture without significant customization efforts. - When looking for specialized RAG platforms that offer more mature features like extensive pre-trained models or advanced data handling specific to niche industries. ## When NOT to use UFO - - If your requirements are limited to simple, quick task execution on a single Windows device, UFO³ might be overkill. Consider using UFO² instead. - - When you prefer a tool without the complexity of DAG-based orchestration and asynchronous task handling; in such cases, simpler automation tools or UFO² may be more appropriate. ## Common questions ### What is the difference between ragflow and UFO? ragflow: Retrieval-Augmented Generation (RAG) engine fusing Agent capabilities with LLM context management. UFO: Weaving the Digital Agent Galaxy. See the comparison table for live GitHub stats and shared categories. ### When should I choose ragflow over UFO? Choose ragflow over UFO when ragflow is primarily Go; UFO is Python; License: ragflow is Apache-2.0, UFO is MIT; Pricing: RAGFlow is offered under an Apache-2.0 license, making the core functionality free and open-source. However, there may be additional costs associated with hosting, infrastructure maintenance, and any云; RAGFlow focuses on Retrieval-Augmented Generation and LLM context management, similar to UFO³'s task focus areas including complex automation and task orchestration; Tags unique to ragflow: context-management, llm-context-layer, rag, agentic-ai; Also covers Data & Retrieval; ragflow ships Docker support for self-hosted deployment; When you need a tool that integrates both retrieval-augmented generation and AI agent functionalities to enhance the contextual layer for any use case involving large language models. ### When should I choose UFO over ragflow? Choose UFO over ragflow when UFO is primarily Python; ragflow is Go; License: UFO is MIT, ragflow is Apache-2.0; RAGFlow focuses on Retrieval-Augmented Generation and LLM context management, similar to UFO³'s task focus areas including complex automation and task orchestration; Tags unique to UFO: windows, llm, gui, copilot; Also covers Developer Tools; - You need to manage complex multi-step automation workflows across multiple devices. ### When should I avoid ragflow? If your project strictly requires a Python environment as RAGFlow is written in Go, transitioning or integrating might pose technical challenges. In situations where you need real-time processing capabilities superior to what's currently offered by RAGFlow’s architecture without significant customization efforts. When looking for specialized RAG platforms that offer more mature features like extensive pre-trained models or advanced data handling specific to niche industries. ### When should I avoid UFO? - If your requirements are limited to simple, quick task execution on a single Windows device, UFO³ might be overkill. Consider using UFO² instead. - When you prefer a tool without the complexity of DAG-based orchestration and asynchronous task handling; in such cases, simpler automation tools or UFO² may be more appropriate. ### Is ragflow or UFO more popular on GitHub? ragflow has more GitHub stars (84,561 vs 9,270). Stars measure visibility, not whether either tool fits your constraints. ### Are ragflow and UFO open source? Yes - both are open-source projects on GitHub (ragflow: Apache-2.0, UFO: MIT). ### Where can I find alternatives to ragflow or UFO? GraphCanon lists graph-backed alternatives at /tools/infiniflow-ragflow/alternatives and /tools/microsoft-ufo/alternatives (/tools/infiniflow-ragflow/alternatives.md, /tools/microsoft-ufo/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/infiniflow-ragflow-vs-microsoft-ufo.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ragflow or UFO? ragflow: Very active. UFO: Very 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 ragflow and UFO? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ragflow: /tools/infiniflow-ragflow/trust; UFO: /tools/microsoft-ufo/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=infiniflow-ragflow`](/api/graphcanon/graph?tool=infiniflow-ragflow) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_