--- title: "plano vs dify" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/katanemo-plano-vs-langgenius-dify" tools: ["katanemo-plano", "langgenius-dify"] --- # plano vs dify Neutral, constraint-first comparison with live GitHub stats. | | [plano](/tools/katanemo-plano.md) | [dify](/tools/langgenius-dify.md) | | --- | --- | --- | | Tagline | AI-native proxy server and data plane for agentic apps | Production-ready platform for agentic workflow development | | Stars | 6,688 | 148,139 | | Forks | 443 | 23,336 | | Open issues | 132 | 813 | | Language | Rust | TypeScript | | Adopt for | Plano is an AI-native proxy server and data plane designed to support agentic applications by handling orchestration, safety, observability, and smart LLM routing. It leverages Rust for efficiency and uses a modular, out | Dify is a production-ready platform for developing AI-driven workflows. It supports both no-code and low-code environments, making it accessible to a wide range of developers and backed by various AI models. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | AI Agents, Evaluation & Observability, Inference & Serving | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [plano](/tools/katanemo-plano.md) | [dify](/tools/langgenius-dify.md) | | --- | --- | --- | | Open issues (now) | 132 | 813 | | Security scan | Not scanned | No MCP manifest | | Full report | [trust report](/tools/katanemo-plano/trust.md) | [trust report](/tools/langgenius-dify/trust.md) | **Typed relationship:** plano _(alternative)_ dify Both Plano and DIFY are platforms aimed at facilitating the development of agentic workflows, with a particular focus on production readiness and orchestration. ## Decision facts: plano - **Adopt for:** Plano is an AI-native proxy server and data plane designed to support agentic applications by handling orchestration, safety, observability, and smart LLM routing. It leverages Rust for efficiency and uses a modular, out ## Decision facts: dify - **Adopt for:** Dify is a production-ready platform for developing AI-driven workflows. It supports both no-code and low-code environments, making it accessible to a wide range of developers and backed by various AI models. ## Choose when ### Choose plano if… - plano is primarily Rust; dify is TypeScript. - License: plano is Apache-2.0, dify is Other. - Both Plano and DIFY are platforms aimed at facilitating the development of agentic workflows, with a particular focus on production readiness and orchestration. - Tags unique to plano: llm-routing, orchestration, proxy-server, observability. - Also covers Evaluation & Observability, Inference & Serving. - plano ships Docker support for self-hosted deployment. - - When you need to decouple essential functionalities such as agent routing, orchestration, moderation policies, and model agility from your application code. ### Choose dify if… - dify is primarily TypeScript; plano is Rust. - License: dify is Other, plano is Apache-2.0. - Both Plano and DIFY are platforms aimed at facilitating the development of agentic workflows, with a particular focus on production readiness and orchestration. - Tags unique to dify: agentic-ai, automation, agent. - - Use Dify when you need a comprehensive environment that combines no-code and low-code development practices with advanced AI capabilities. ## When NOT to use plano - - If your project requires only basic functionalities without advanced orchestration or model management, Plano's comprehensive features may introduce unnecessary complexity. - - When focusing on a specific language or framework that does not benefit significantly from the modular and multi-framework support offered by Plano. - - For scenarios where the additional layer of an out-of-process data plane might increase latency beyond acceptable levels for your application. ## When NOT to use dify - - Avoid using Dify if your project requires heavy customization that goes beyond what is provided by the platform’s no-code and low-code frameworks. - - If your team prefers a self-hosted solution with full control over the environment, but Dify's hosted cloud model might not offer sufficient flexibility for your specific needs. ## Common questions ### What is the difference between plano and dify? plano: AI-native proxy server and data plane for agentic apps. dify: Production-ready platform for agentic workflow development. See the comparison table for live GitHub stats and shared categories. ### When should I choose plano over dify? Choose plano over dify when plano is primarily Rust; dify is TypeScript; License: plano is Apache-2.0, dify is Other; Both Plano and DIFY are platforms aimed at facilitating the development of agentic workflows, with a particular focus on production readiness and orchestration; Tags unique to plano: llm-routing, orchestration, proxy-server, observability; Also covers Evaluation & Observability, Inference & Serving; plano ships Docker support for self-hosted deployment; - When you need to decouple essential functionalities such as agent routing, orchestration, moderation policies, and model agility from your application code. ### When should I choose dify over plano? Choose dify over plano when dify is primarily TypeScript; plano is Rust; License: dify is Other, plano is Apache-2.0; Both Plano and DIFY are platforms aimed at facilitating the development of agentic workflows, with a particular focus on production readiness and orchestration; Tags unique to dify: agentic-ai, automation, agent; - Use Dify when you need a comprehensive environment that combines no-code and low-code development practices with advanced AI capabilities. ### When should I avoid plano? - If your project requires only basic functionalities without advanced orchestration or model management, Plano's comprehensive features may introduce unnecessary complexity. - When focusing on a specific language or framework that does not benefit significantly from the modular and multi-framework support offered by Plano. - For scenarios where the additional layer of an out-of-process data plane might increase latency beyond acceptable levels for your application. ### When should I avoid dify? - Avoid using Dify if your project requires heavy customization that goes beyond what is provided by the platform’s no-code and low-code frameworks. - If your team prefers a self-hosted solution with full control over the environment, but Dify's hosted cloud model might not offer sufficient flexibility for your specific needs. ### Is plano or dify more popular on GitHub? dify has more GitHub stars (148,139 vs 6,688). Stars measure visibility, not whether either tool fits your constraints. ### Are plano and dify open source? Yes - both are open-source projects on GitHub (plano: Apache-2.0, dify: Other). ### Where can I find alternatives to plano or dify? GraphCanon lists graph-backed alternatives at /tools/katanemo-plano/alternatives and /tools/langgenius-dify/alternatives (/tools/katanemo-plano/alternatives.md, /tools/langgenius-dify/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/katanemo-plano-vs-langgenius-dify.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, plano or dify? plano: Very active. dify: 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 plano and dify? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: plano: /tools/katanemo-plano/trust; dify: /tools/langgenius-dify/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=katanemo-plano`](/api/graphcanon/graph?tool=katanemo-plano) - 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/_