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