Comparison
ruoyi-ai vs dify
Verdict
Pick ruoyi-ai if ruoyi-ai is an enterprise-focused all-in-one AI app development framework with support for model management, multi-agent collaboration, and RAG technology; pick dify if dify is a comprehensive low-code/no-code AI agentic framework designed for workflow and process automation, offering deployment via Docker Compose and multiple cloud platforms.
Markdown twin · ruoyi-ai alternatives · dify alternatives
GraphCanon updated Sep 8, 2026
Trust & integrity
| Signal | ruoyi-ai | dify |
|---|---|---|
| Maintenance | Very active (2d since push) As of Sep 8, 2026 · github_public_v1 | Very active (0d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 8, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 26, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- ruoyi-ai
- 一站式AI应用开发框架
- dify
- Production-ready platform for agentic workflow development
Stars
- ruoyi-ai
- 5.7k
- dify
- 155k
Forks
- ruoyi-ai
- 1.4k
- dify
- 24k
Open issues
- ruoyi-ai
- 4
- dify
- 1.1k
Language
- ruoyi-ai
- Java
- dify
- TypeScript
Adopt for
- ruoyi-ai
- Ruoyi-ai is an enterprise-focused all-in-one AI app development framework with support for model management, multi-agent collaboration, and RAG technology.
- dify
- Dify is a comprehensive low-code/no-code AI agentic framework designed for workflow and process automation, offering deployment via Docker Compose and multiple cloud platforms.
Persona
- ruoyi-ai
- -
- dify
- -
Runtime
- ruoyi-ai
- -
- dify
- -
License
- ruoyi-ai
- MIT
- dify
- Other
Last pushed
- ruoyi-ai
- Sep 5, 2026
- dify
- Sep 7, 2026
Categories
- ruoyi-ai
- Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training
- dify
- AI Agents
Trust and health
Days since push
- ruoyi-ai
- 2d
- dify
- 0d
Open issues (now)
- ruoyi-ai
- 4
- dify
- 1.1k
Stars delta
- ruoyi-ai
- +73 (30d)
- dify
- +3.0k (30d)
Open issues delta
- ruoyi-ai
- +3 (30d)
- dify
- +122 (30d)
Owner type
- ruoyi-ai
- User
- dify
- Organization
Full report
- ruoyi-ai
- Trust report
- dify
- Trust report
Choose ruoyi-ai if…
- ruoyi-ai is primarily Java; dify is TypeScript.
- License: ruoyi-ai is MIT, dify is Other.
- Tags unique to ruoyi-ai: ai, knowledge, mcp, rag.
- Also covers Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training.
- When you need to integrate multiple vendor models into a single platform
When NOT to use ruoyi-ai
- Avoid if only simple AI functionalities are needed without complex model integration or management
- Not recommended for teams preferring non-Java ecosystems as the platform is Java-centric
- If immediate deployment and setup speed are critical, due to its enterprise-grade extensive features
Choose dify if…
- dify is primarily TypeScript; ruoyi-ai is Java.
- License: dify is Other, ruoyi-ai is MIT.
- Requirements: Min 4 GB RAM; Requires Docker.
- Tags unique to dify: agentic-ai, agentic-framework, automation, gemini.
- Also covers AI Agents.
- When you need a production-grade platform with support for various deployment methods such as Docker Compose, Kubernetes Helm Charts, Terraform, AWS CDK, and Alibaba Cloud services.
When NOT to use dify
- If your project strictly requires a specific proprietary licensing scheme not aligned with Dify’s customized open-source license that is based on Apache 2.0.
- In cases where the desired workflow development tool should be written in a language other than TypeScript or Python, as Dify centers primarily around these languages.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ageerle/ruoyi-ai) · observed Sep 8, 2026
- GitHub forks (ageerle/ruoyi-ai) · observed Sep 8, 2026
- Last push (ageerle/ruoyi-ai) · observed Sep 5, 2026
- License file (MIT) · observed Sep 8, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 26, 2026
- GitHub stars (langgenius/dify) · observed Sep 7, 2026
- GitHub forks (langgenius/dify) · observed Sep 7, 2026
- Last push (langgenius/dify) · observed Sep 7, 2026
- License file (Other) · observed Sep 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ruoyi-ai 5.7k · dify 155k (synced Sep 8, 2026).
Common questions
- What is the difference between ruoyi-ai and dify?
- ruoyi-ai: 一站式AI应用开发框架. dify: Production-ready platform for agentic workflow development. See the comparison table for live GitHub stats and shared categories.
- When should I choose ruoyi-ai over dify?
- Choose ruoyi-ai over dify when ruoyi-ai is primarily Java; dify is TypeScript; License: ruoyi-ai is MIT, dify is Other; Tags unique to ruoyi-ai: ai, knowledge, mcp, rag; Also covers Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training; When you need to integrate multiple vendor models into a single platform.
- When should I choose dify over ruoyi-ai?
- Choose dify over ruoyi-ai when dify is primarily TypeScript; ruoyi-ai is Java; License: dify is Other, ruoyi-ai is MIT; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to dify: agentic-ai, agentic-framework, automation, gemini; Also covers AI Agents; When you need a production-grade platform with support for various deployment methods such as Docker Compose, Kubernetes Helm Charts, Terraform, AWS CDK, and Alibaba Cloud services.
- When should I avoid ruoyi-ai?
- Avoid if only simple AI functionalities are needed without complex model integration or management Not recommended for teams preferring non-Java ecosystems as the platform is Java-centric If immediate deployment and setup speed are critical, due to its enterprise-grade extensive features
- When should I avoid dify?
- If your project strictly requires a specific proprietary licensing scheme not aligned with Dify’s customized open-source license that is based on Apache 2.0. In cases where the desired workflow development tool should be written in a language other than TypeScript or Python, as Dify centers primarily around these languages.
- Is ruoyi-ai or dify more popular on GitHub?
- dify has more GitHub stars (154,714 vs 5,683). Stars measure visibility, not whether either tool fits your constraints.
- Are ruoyi-ai and dify open source?
- Yes - both are open-source projects on GitHub (ruoyi-ai: MIT, dify: Other).
- Where can I find alternatives to ruoyi-ai or dify?
- GraphCanon lists graph-backed alternatives at ruoyi-ai alternatives and dify alternatives (ruoyi-ai markdown twin, dify markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, ruoyi-ai or dify?
- ruoyi-ai: 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 ruoyi-ai and dify?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ruoyi-ai trust report; dify trust report.