Flowise vs n8n
Side-by-side comparison of two AI agent tools
Flowisefree
Build AI Agents, Visually
n8nfree
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
Metrics
| Flowise | n8n | |
|---|---|---|
| Stars | 51.1k | 181.4k |
| Star velocity /mo | 4.3k | 15.1k |
| Commits (90d) | — | — |
| Releases (6m) | 7 | 10 |
| Overall score | 0.7661078272950179 | 0.8257313925210539 |
Pros
- +可视化拖拽界面，降低AI智能体开发门槛，无需编程背景即可使用
- +支持多种部署选项，包括本地安装、Docker容器和云端服务，适应不同使用场景
- +活跃的开源社区支持，GitHub上51k+星标显示了强大的用户基础和持续维护
- +Hybrid approach combining visual workflow building with full JavaScript/Python coding capabilities when needed
- +AI-native platform with LangChain integration for building sophisticated AI agent workflows using custom data and models
- +Fair-code license ensures source code transparency with self-hosting options, providing data control and deployment flexibility
Cons
- -需要Node.js 18.15.0+运行环境，对系统环境有一定技术要求
- -复杂的多模块架构可能对简单用例造成过度工程化
- -文档和功能细节有限，可能需要额外学习成本
- -Requires technical knowledge to fully leverage coding capabilities and advanced features
- -Self-hosting demands infrastructure management and maintenance overhead
- -Fair-code license restricts commercial usage at scale without enterprise licensing
Use Cases
- •企业级AI客服机器人快速搭建，通过可视化流程设计对话逻辑
- •数据分析工作流自动化，连接多个AI模型进行复合分析任务
- •教育培训场景中的AI助手原型开发，用于概念验证和演示
- •Building AI agent workflows that process customer data using LangChain and custom language models
- •Automating complex business processes that require both API integrations and custom business logic
- •Creating data synchronization pipelines between multiple SaaS tools while maintaining full control over sensitive data through self-hosting