--- title: "ragflow vs kedro" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/infiniflow-ragflow-vs-kedro-org-kedro" tools: ["infiniflow-ragflow", "kedro-org-kedro"] --- # ragflow vs kedro *GraphCanon updated Jul 11, 2026* ## Verdict Pick ragflow when ragflow is primarily Go; kedro is Python; pick kedro when kedro is primarily Python; ragflow is Go. [ragflow](https://ragflow.io) reports 85k GitHub stars, 9.9k forks, and 2.3k open issues, last pushed Jul 11, 2026. [kedro](https://kedro.org) has 11k stars, 1.1k forks, and 161 open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [ragflow's repository](https://github.com/infiniflow/ragflow) and [kedro's repository](https://github.com/kedro-org/kedro). | | [ragflow](/tools/infiniflow-ragflow.md) | [kedro](/tools/kedro-org-kedro.md) | | --- | --- | --- | | Tagline | Retrieval-Augmented Generation engine with agent capabilities | Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, an | | Stars | 84,818 | 10,911 | | Forks | 9,905 | 1,050 | | Open issues | 2,302 | 161 | | Language | Go | Python | | Adopt for | RAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released under the Apache-2.0 license. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License | Apache-2.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ragflow](/tools/infiniflow-ragflow.md) | [kedro](/tools/kedro-org-kedro.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 2.3k | 161 | | Security scan | 4 low (4 low) | No lockfile | | Full report | [trust report](/tools/infiniflow-ragflow/trust.md) | [trust report](/tools/kedro-org-kedro/trust.md) | ## Decision facts: ragflow - **Requirements:** Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services. - **Adopt for:** RAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released under the Apache-2.0 license. - **License detail:** Apache-2.0 License ## Choose when ### Choose ragflow if… - ragflow is primarily Go; kedro is Python. - Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.. - Tags unique to ragflow: context-management, rag, retrieval-augmented-generation. - ragflow ships Docker support for self-hosted deployment. - - You need an integrated RAG system with AI agent capabilities for better context management in your applications. ### Choose kedro if… - kedro is primarily Python; ragflow is Go. - Tags unique to kedro: machine-learning, agentic-workflow, hacktoberfest, kedro. - Leaner open-issue backlog (161). ## When NOT to use ragflow - - If you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go. - - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB). - - You cannot use external LLM services and embedding services, as RAGFlow relies on them to function. ## When NOT to use kedro - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ## Common questions ### What is the difference between ragflow and kedro? ragflow: Retrieval-Augmented Generation engine with agent capabilities. kedro: Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, an. See the comparison table for live GitHub stats and shared categories. ### When should I choose ragflow over kedro? Choose ragflow over kedro when ragflow is primarily Go; kedro is Python; Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.; Tags unique to ragflow: context-management, rag, retrieval-augmented-generation; ragflow ships Docker support for self-hosted deployment; - You need an integrated RAG system with AI agent capabilities for better context management in your applications. ### When should I choose kedro over ragflow? Choose kedro over ragflow when kedro is primarily Python; ragflow is Go; Tags unique to kedro: machine-learning, agentic-workflow, hacktoberfest, kedro; Leaner open-issue backlog (161). ### When should I avoid ragflow? - If you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go. - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB). - You cannot use external LLM services and embedding services, as RAGFlow relies on them to function. ### When should I avoid kedro? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. ### Is ragflow or kedro more popular on GitHub? ragflow has more GitHub stars (84,818 vs 10,911). Stars measure visibility, not whether either tool fits your constraints. ### Are ragflow and kedro open source? Yes - both are open-source projects on GitHub (ragflow: Apache-2.0, kedro: Apache-2.0). ### Where can I find alternatives to ragflow or kedro? GraphCanon lists graph-backed alternatives at [ragflow alternatives](/tools/infiniflow-ragflow/alternatives) and [kedro alternatives](/tools/kedro-org-kedro/alternatives) ([ragflow markdown twin](/tools/infiniflow-ragflow/alternatives.md), [kedro markdown twin](/tools/kedro-org-kedro/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 [this comparison](/compare/infiniflow-ragflow-vs-kedro-org-kedro.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ragflow or kedro? ragflow: Very active. kedro: 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 kedro? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ragflow trust report](/tools/infiniflow-ragflow/trust); [kedro trust report](/tools/kedro-org-kedro/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/_