THE COMPARISON / A CLOSER LOOK

Langflow vs n8n

Compare the listed plans, useful capabilities, and practical tradeoffs.

Prices and features reflect editorial records. Check vendor terms before you buy; documentary checks do not imply hands-on testing.

Langflow

🟡Low Code

AI Agents

Open-source visual editor (acquired by DataStax/IBM) for building, prototyping, and deploying agentic LLM workflows with hundreds of pre-built components.

SOURCE-CHECK COVERAGE

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Starting Price

Free

n8n

🟡Low Code

AI Automation

Source-available workflow automation platform with native AI agent and LangChain nodes, popular for self-hosted AI workflows.

SOURCE-CHECK COVERAGE

No scoped source-check record shown. Check current pricing and vendor terms before buying.

Starting Price

Free

Feature Comparison

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FeatureLangflown8n
CategoryAI AgentsAI Automation
Pricing Plans2 listed plans4 listed plans
Starting PriceFreeFree
Key Features
  • • Low-code visual builder for agentic and RAG applications
  • • Build and deploy AI agents and MCP servers
  • • Supports major LLMs, vector databases, and AI tools
  • • Visual AI-agent canvas with traceable steps
  • • 500+ integrations and 10,000 workflow templates
  • • JavaScript, Python, HTTP, webhook, API, and CLI escape hatches

Langflow - Pros & Cons

Pros

  • ✓Lowest-friction path to functional LLM agents for non-engineers
  • ✓MIT-licensed core with no artificial feature gating versus the cloud version
  • ✓Bi-directional MCP support is rare — most builders are MCP clients only
  • ✓Inline custom Python escape hatch means you're not stuck inside the visual paradigm
  • ✓Backed by IBM/DataStax means long-term maintenance is well funded

Cons

  • ✗Visual flows become unwieldy past ~30 nodes; refactoring is awkward
  • ✗Component quality varies — community contributions can be uneven
  • ✗Self-hosted observability is limited; you'll want LangSmith or Langfuse alongside
  • ✗Versioning of flows is JSON-export based, not git-native
  • ✗Performance overhead versus hand-written code is non-trivial at scale

n8n - Pros & Cons

Pros

  • ✓Self-hosted Community edition is free and runs anywhere — no per-task pricing tax
  • ✓Native AI Agent node and LangChain blocks let you build real agents on a visual canvas
  • ✓MCP Client node integrates n8n into the emerging MCP agent ecosystem
  • ✓JavaScript code nodes provide escape hatches for anything the visual editor cannot express

Cons

  • ✗Visual editor becomes noisy on workflows with dozens of branches and tool calls
  • ✗Debugging long-running agent loops is still painful versus a real code IDE
  • ✗Cloud tier execution caps can surprise heavy users — self-hosting is the practical path at scale
  • ✗Sustainable Use License is fair-code, not OSI-approved open source, which some procurement teams flag

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🔒 Security & Compliance Comparison

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Security FeatureLangflown8n
SOC2——
GDPR——
HIPAA——
SSO—✅ Yes
Self-Hosted✅ Yes🔀 Hybrid
On-Prem✅ Yes✅ Yes
RBAC—✅ Yes
Audit Log—✅ Yes
Open Source✅ Yes❌ No
API Key Auth✅ Yes✅ Yes
Encryption at Rest—✅ Yes
Encryption in Transit—✅ Yes
Data Residency—EU
Data Retentionconfigurableconfigurable
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