Apache Airflow vs Temporal
Apache Airflow
Programmatic workflow orchestration for data pipelines
Temporal
Durable workflow execution platform for microservices
| Feature | Apache Airflow | Temporal |
|---|---|---|
| Category | Automation | Automation |
| Sub-category | Workflow | Workflow |
| Maturity | stable | stable |
| Complexity | intermediate | intermediate |
| Performance tier | medium | medium |
| License | Apache-2.0 | MIT |
| License type | permissive | permissive |
| Pricing | fully free | fully free |
| GitHub stars | 38.0K | 13.0K |
| Contributors | 0 | 0 |
| Commit frequency | weekly | weekly |
| Plugin ecosystem | none | none |
| Docs quality | good | good |
| Backing org | Apache Foundation | Temporal Technologies |
| Funding model | foundation | vc_backed |
| Min RAM | 2 GB | 2 GB |
| Min CPU cores | 2 | 2 |
| 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 | Go |
| 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 Temporal
- ✓ Primary: long-running-workflows
- ✓ Primary: microservice-orchestration
- ✓ Primary: saga-pattern
Apache Airflow anti-patterns
- ✕ Not for real-time streaming
- ✕ Complex setup and operations
- ✕ DAG parsing can be slow
- ✕ Not for event-driven workflows
Temporal anti-patterns
- ✕ Complex to operate in production
- ✕ Steep learning curve
- ✕ Overkill for simple automations