Apache Airflow vs n8n

Apache Airflow

Programmatic workflow orchestration for data pipelines

n8n

Fair-code workflow automation with 400+ integrations

Feature Apache Airflow n8n
Category Automation Automation
Sub-category Workflow Workflow
Maturity stable stable
Complexity intermediate intermediate
Performance tier medium medium
License Apache-2.0 Sustainable Use
License type permissive fair-code
Pricing fully free fully free
GitHub stars 38.0K 55.0K
Contributors 0 0
Commit frequency weekly weekly
Plugin ecosystem none none
Docs quality good good
Backing org Apache Foundation n8n GmbH
Funding model foundation vc_backed
Min RAM 2 GB 512 MB
Min CPU cores 2 1
Scaling pattern single_node single_node
Self-hostable Yes Yes
K8s native No No
Offline capable No No
Vendor lock-in none none
Languages Python TypeScript
API type REST REST
Protocols HTTP HTTP
Deployment docker, pip docker, npm
SDK languages — —
Team size fit solo, small, medium, enterprise solo, small, medium, enterprise
First release 2020 2020
Latest version — —

When to use Apache Airflow

  • ✓ Primary: data-pipeline-orchestration
  • ✓ Primary: etl-scheduling
  • ✓ Primary: ml-pipeline-management

When to use n8n

  • ✓ Primary: api-integration
  • ✓ Primary: business-process-automation
  • ✓ Primary: ai-workflow-building

Apache Airflow anti-patterns

  • ✕ Not for real-time streaming
  • ✕ Complex setup and operations
  • ✕ DAG parsing can be slow
  • ✕ Not for event-driven workflows

n8n anti-patterns

  • ✕ Fair-code license restricts some commercial use
  • ✕ Complex workflows can be hard to debug
  • ✕ Self-hosting needs maintenance
Full Apache Airflow profile → Full n8n profile → All comparisons