Dify vs 
Kestra
Dify vs Kestra compared for 2026 — features, license, ease of use, performance and which one to choose. Build and operate AI apps visually vs Declarative orchestration with AI steps.
Updated regularly · curated by OpenSourceAI.tech
Dify vs Kestra at a glance
| Spec | Dify | Kestra |
|---|---|---|
| Category | Low-code AI builder | Low-code AI builder |
| Type | LLMOps platform | Orchestration platform |
| License | Apache-2.0 | Apache-2.0 |
| Runs locally | Self-hosted | Yes |
| Primary language | Python / TS | Java |
| Ease of use | Beginner | Intermediate |
| Best for | teams shipping production AI apps with less code | data pipelines that include AI steps |
| GitHub stars | 149.1k | 27.4k |
How Dify and Kestra score
| Criterion | Dify | Kestra |
|---|---|---|
| Popularity | 5.0 | 3.5 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 5.0 | 3.5 |
| Privacy | 4.5 | 5.0 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
Dify
Dify is an open-source LLMOps platform to visually build, deploy and operate AI applications and agents, with RAG, workflows and observability built in.
- Full LLMOps: build, deploy and monitor
- Visual workflows plus built-in RAG
- Production-oriented with observability
Kestra
Kestra orchestrates data and AI workflows declaratively in YAML, with a UI, scheduling and hundreds of plugins.
- Declarative YAML workflows
- Handles large data pipelines
- Rich plugin ecosystem
Key differences
Dify is lLMOps platform, while Kestra is orchestration platform. Dify leans more beginner-friendly, whereas Kestra is more suited to intermediate users. They also differ in how they run (Self-hosted vs Yes). In short, Dify fits teams shipping production AI apps with less code, and Kestra fits data pipelines that include AI steps.
Which should you choose?
Choose Dify for teams shipping production AI apps with less code. Choose Kestra for data pipelines that include AI steps.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is Dify or Kestra easier to use?
Dify is generally the easier of the two to get started with, while Kestra rewards more setup with more control.
Are Dify and Kestra free?
Dify is free and open source (Apache-2.0), and Kestra is free and open source (Apache-2.0). Neither charges for the core software.
Can I run Dify and Kestra locally?
Dify: self-hosted · Kestra: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
Dify vs Kestra — which should I pick in 2026?
Choose Dify for teams shipping production AI apps with less code. Choose Kestra for data pipelines that include AI steps.
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