Apache Airflow vs AWS Step Functions
A side-by-side comparison of Apache Airflow and AWS Step Functions across 26 workflow orchestration capabilities. Apache Airflow fully supports 13 of them and AWS Step Functions fully supports 18; of the 12 mandatory features, Apache Airflow covers 11 and AWS Step Functions covers 10.
Apache Airflow
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It allows you to define workflows as code, making them more maintainable, versionable, testable, and collaborative.
AWS Step Functions
AWS Step Functions is a fully managed, serverless workflow orchestration service that coordinates AWS services, Lambda functions and microservices using state machines defined in Amazon States Language.
Feature comparison
14 of 26 capabilities differ between Apache Airflow and AWS Step Functions.
| Capability | Importance* | Apache Airflow | AWS Step Functions |
|---|---|---|---|
DAG-based workflow definition Define dependencies and execution order Mandatory | Mandatory | Yes | Partial |
Code-first workflows Versionable, testable workflows Mandatory | Mandatory | Yes | Partial |
Declarative workflow model Predictability, reproducibility Mandatory | Mandatory | Yes | Yes |
Task dependency resolution Correct execution order Mandatory | Mandatory | Yes | Yes |
Persistent workflow state Crash recovery, observability Mandatory | Mandatory | Yes | Yes |
Task retries Handle transient failures Mandatory | Mandatory | Yes | Yes |
Retry policies (backoff, limits) Avoid cascading failures Recommended | Recommended | Partial | Yes |
Scheduling (cron / time-based) Automated recurring workflows Depends | Depends | Yes | Partial |
Event-driven execution React to external systems Depends | Depends | Partial | Yes |
Backfills / replays Reprocess historical data Depends | Depends | Yes | No |
Idempotency support Safe retries & replays Mandatory | Mandatory | Yes | Yes |
Exactly-once semantics Correctness for business workflows Optional | Optional | No | Yes |
Long-running workflows (days/months) Business processes, approvals Depends | Depends | No | Yes |
Human-in-the-loop steps Approvals, manual actions Optional | Optional | No | Yes |
Dynamic workflows at runtime Conditional execution Depends | Depends | Partial | Partial |
Workflow versioning Safe evolution over time Recommended | Recommended | No | Yes |
Distributed execution Scalability Mandatory | Mandatory | Yes | Yes |
High availability scheduler Production reliability Recommended | Recommended | Partial | Yes |
Fault-tolerant execution Crash safety Mandatory | Mandatory | Partial | Yes |
Observability (logs, states, UI) Debugging & ops Mandatory | Mandatory | Yes | Yes |
Workflow-level visibility Understand end-to-end runs Mandatory | Mandatory | Yes | Yes |
Task isolation Failure containment Mandatory | Mandatory | Yes | Yes |
Native Kubernetes support Modern infra compatibility Depends | Depends | Partial | Partial |
Multi-language SDKs Polyglot systems Optional | Optional | No | Yes |
Deterministic replay Safe recovery & correctness Optional | Optional | No | No |
Pluggable execution backends Flexibility Recommended | Recommended | Partial | No |
* To be considered a complete workflow orchestration tool, a tool must implement the features marked as mandatory according to our assessment.
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Read the full profiles, including pros and cons, installation and alternatives.
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