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Dify vs Flowise
Side-by-side comparison of Dify and Flowise — features, pricing, performance scores, and which to choose for your AI agents.
View All Framework ComparisonsQuick Verdict
| Dimension | Dify | Flowise | Winner |
|---|---|---|---|
Ease of Use | 4/5 | 5/5 | Flowise |
Scalability | 5/5 | 3/5 | Dify |
Documentation | 5/5 | 4/5 | Dify |
Community | 5/5 | 4/5 | Dify |
Performance | 4/5 | 3/5 | Dify |
Overall: Dify wins 4 categories, Flowise wins 1, 0 tied
Feature Comparison
| Feature | Dify | Flowise |
|---|---|---|
| Primary Language | Python | TypeScript |
| License | Apache-2.0 | Apache-2.0 |
| Pricing | Open Source + Cloud | Open Source + Cloud |
| GitHub Stars | 100,000 | 30,000 |
| Difficulty | Intermediate | Beginner |
| Enterprise Ready | ||
| Community Size | Very Large | Large |
| Category | Visual Development | Visual Development |
Pros & Cons
Dify
Advantages
Comprehensive LLMOps platform
Visual agent building with code flexibility
Strong community (100k+ stars)
Apache 2.0 license
Production-ready with observability
Multi-agent orchestration
Cloud and self-host options
Limitations
Can be complex to set up initially
Docker-based deployment required
Learning curve for full platform
Cloud pricing for managed version
Flowise
Advantages
Very low barrier to entry with drag-and-drop
Integrates well with LangChain and LlamaIndex
Good for rapid prototyping
Active development and updates
Open source under Apache 2.0
Limitations
Less suitable for production-grade applications
Limited customization compared to code-first approaches
Performance overhead from visual layer
Smaller community than LangChain
Documentation could be more comprehensive
Self-hosting requires infrastructure management
Best Use Cases
Dify
LLMOps and model management
Visual agent building
RAG applications
Multi-agent orchestration
Internal AI tools and assistants
API-based AI services
Flowise
RAG applications for document Q&A
Chatbots and conversational interfaces
Rapid prototyping of AI applications
API-based AI services
Knowledge base assistants
Visual workflow design for non-developers
Getting Started
Dify
Installation
docker-compose up or pip install
Flowise
Installation
npm install -g flowise
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