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Langflow vs n8n
Side-by-side comparison of Langflow and n8n — features, pricing, performance scores, and which to choose for your AI agents.
View All Framework ComparisonsQuick Verdict
| Dimension | Langflow | n8n | Winner |
|---|---|---|---|
Ease of Use | 5/5 | 5/5 | Tie |
Scalability | 4/5 | 4/5 | Tie |
Documentation | 4/5 | 5/5 | n8n |
Community | 5/5 | 5/5 | Tie |
Performance | 4/5 | 4/5 | Tie |
Overall: Langflow wins 0 categories, n8n wins 1, 4 tied
Feature Comparison
| Feature | Langflow | n8n |
|---|---|---|
| Primary Language | Python | TypeScript |
| License | MIT | Fair-code (Sustainable Use License + Enterprise) |
| Pricing | Open Source | Freemium |
| GitHub Stars | 44,100 | 49,500 |
| Difficulty | Beginner | Beginner |
| Enterprise Ready | ||
| Community Size | Very Large | Very Large |
| Category | Visual Development | Workflow Orchestration |
Pros & Cons
Langflow
Advantages
Very high GitHub stars (44k+) indicates strong adoption
Low-code visual interface lowers barrier to entry
Full Python customization maintains developer flexibility
All flows are JSON - easy to share and version control
Multiple deployment options (API MCP embedded)
Open source with MIT license
Active development and regular updates
Supports all major LLMs and vector databases
Limitations
Visual interface can be limiting for very complex logic
Requires Python knowledge for advanced customization
Team collaboration features are limited
Documentation still growing
Self-hosting requires infrastructure management
No built-in authentication for shared instances
Performance overhead from visual layer
n8n
Advantages
Fair-code license allows self-hosting with source access
400+ pre-built integrations reduce development time
Visual interface lowers barrier to entry
Strong community with active development
Native AI capabilities built-in
Can write custom code when needed
Enterprise-ready with commercial support
Self-host or cloud options available
Limitations
Fair-code license has restrictions for commercial offerings
Visual interface can be limiting for very complex logic
Learning curve for advanced workflow patterns
Cloud pricing can escalate with usage
Some integrations require manual configuration
Less suitable for pure code-first development
Best Use Cases
Langflow
RAG applications for document Q&A
Chatbots and conversational interfaces
Multi-agent workflows
Rapid prototyping of AI applications
API-based AI services
Internal tools and automation
n8n
Business process automation
API integration and data synchronization
Marketing automation workflows
Customer data management
E-commerce automation
Internal tool integration
Getting Started
Langflow
Installation
pip install langflow
n8n
Installation
npm install n8n -g
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