n8n (8.0/10) vs LangFlow (8.2/10) — extremely close. n8n stands out with visual workflow builder and 400+ integrations. LangFlow wins on visual drag-and-drop flow builder with LangFlow is cheaper to self-host. Your choice depends on whether you prioritize approach.
| Feature | n8n | LangFlow |
|---|---|---|
| Primary Use Case | General-purpose workflow automation platform with 400+ integrations and AI nodes for connecting business tools | Visual framework for building multi-agent and RAG applications with a Python-based drag-and-drop UI |
| GitHub Stars | 42,000+ | 35,000+ |
| Integrations | 400+ | 100+ |
| Language | TypeScript | Python |
| License | Sustainable Use License (Fair-code) | MIT |
| Min RAM | 2GB | 1GB |
| Docker Image Size | ~850MB | ~650MB |
| Self-Host Cost | $15/mo | $10/mo |
| Cloud Pricing | $20/mo | N/A (self-host only) |
| Ease of Use | 7.5/10 | 8.5/10 |
| AI Capabilities | 7/10 | 8.5/10 |
| Community Score | 8.5/10 | 8/10 |
| Contributors | 400+ | 200+ |
Both tools are free to self-host. The real cost is infrastructure. Here's what you'll actually pay:
Skip the DevOps entirely. Deploy n8n and LangFlow with one click, persistent storage included, auto-SSL, and subdomain routing — starting at $9.99/month.
Teams needing complex business automation with AI capabilities and 400+ service integrations. Key features include visual workflow builder, 400+ native integrations, ai/llm nodes (openai, anthropic, gemini), making it the go-to choice for AI development workflows.
Python developers wanting a visual way to build and iterate on LangChain-based LLM applications. It stands out with visual drag-and-drop flow builder, python-native components, multi-agent orchestration, making it ideal for LLM-powered applications.
You need the strengths of both. n8n handles visual workflow builder while LangFlow provides visual drag-and-drop flow builder. Many production teams combine them via APIs for a complete AI stack.
Persistent storage. Auto-SSL. Subdomain routing. No DevOps required.
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