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AWS Step Functions vs Apache Airflow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

No sentiment score available
Sentiment score
9.5
AWS Step Functions reduce development time and costs, enhance scalability and reliability, streamline workflows, and improve ROI.
 

Customer Service

Sentiment score
7.2
Apache Airflow users value its robust community, documentation, and online resources, resolving issues mostly without commercial support.
Sentiment score
6.4
AWS Step Functions' customer service is mostly positive, with praised enterprise support and mixed reviews on smaller-scale responsiveness.
I use enterprise support, which is excellent, providing responses within fifteen minutes.
 

Scalability Issues

No sentiment score available
Sentiment score
7.8
AWS Step Functions is highly scalable and cost-effective, adapting seamlessly to demand fluctuations for teams of all sizes.
They can handle multiple simultaneous requests effectively.
 

Stability Issues

No sentiment score available
Sentiment score
8.5
AWS Step Functions are rated highly stable by users, ensured by redundancy and strategies for high availability and reliability.
If one zone fails, others handle the demand, ensuring high availability.
 

Room For Improvement

AWS Step Functions requires improvements in data limits, pricing, features, integrations, IDE support, and hybrid cloud integration.
 

Setup Cost

Apache Airflow is a cost-effective, flexible open-source solution valued for local or cloud deployment with optional commercial support.
AWS Step Functions pricing varies based on requests and workflow duration, requiring careful configuration to avoid unpredictable costs.
Pricing for Step Functions is very cheap.
The cost is average, provided it is configured correctly.
 

Valuable Features

AWS Step Functions seamlessly integrate AWS tools, enhancing workflow efficiency with scalable task management, visualization, and error handling.
AWS Step Functions offers advanced workflows that save time and enhance efficiency by reducing delays and ensuring consistent orchestration among various services.
Step Functions provide seamless integration with AWS services, which enhances the speed of application development.
 

Categories and Ranking

Apache Airflow
Ranking in Business Process Management (BPM)
2nd
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
36
Ranking in other categories
No ranking in other categories
AWS Step Functions
Ranking in Business Process Management (BPM)
12th
Average Rating
8.2
Reviews Sentiment
7.3
Number of Reviews
12
Ranking in other categories
Workload Automation (15th)
 

Mindshare comparison

As of December 2024, in the Business Process Management (BPM) category, the mindshare of Apache Airflow is 7.1%, down from 9.2% compared to the previous year. The mindshare of AWS Step Functions is 2.3%, down from 3.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Business Process Management (BPM)
 

Featured Reviews

Sanket Suhagiya - PeerSpot reviewer
Efficient pipeline building with intuitive UI and powerful Python features
The declarative language in Python is very powerful as the learning curve is really less. The UI is also very intuitive, and it makes sense. The core features are strong, which are supported by Apache Airflow variables, DAGs, and connections. Connections make it really extendable to plug-ins and custom modules we can write around it.
Mahender Nirwan - PeerSpot reviewer
Good integration with many AWS services and create a workflow to call one Lambda function after another, and other serverless features
There are two main features I like. You can use the UI or write basic JSON to define the workflow. If you write JSON, it converts it into a visual workflow in the UI. This allows you to visualize what's happening. When you get an error, it's easy to find in any large workflow, and debugging is also pretty easy. I like their UI, to be honest. It has the best profit UI.
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
14%
Manufacturing Company
7%
Healthcare Company
5%
Financial Services Firm
33%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which would you choose - Camunda Platform or Apache Airflow?
Camunda Platform allows for visual demonstration and presentation of business process flows. The flexible Java-based option was a big win for us and allows for the integration of microservices very...
What do you like most about Apache Airflow?
Apache Airflow is easy to use and can monitor task execution easily. For instance, when performing setup tasks, you can conveniently view the logs without delving into the job details.
What is your experience regarding pricing and costs for Apache Airflow?
Apache Airflow is open-source and free. Hyperscalers like Google (with Composer), Azure, and AWS offer managed Airflow services.
What do you like most about Amazon Step Functions?
The integration capability is easy, whereas building state machines is tricky.
What is your primary use case for Amazon Step Functions?
AWS Step Functions is a useful tool for orchestration, particularly when using various AWS services. It helps create workflows and manage the order between services like Lambda and Glue jobs.
What advice do you have for others considering Amazon Step Functions?
Overall, I rate Step Functions nine out of ten. Such ratings are subjective, and I generally do not rate any service a ten out of ten.
 

Also Known As

Airflow
Amazon Step Functions, Step Functions
 

Overview

 

Sample Customers

Agari, WePay, Astronomer
Alpha Apps, The Guardian, SGK, Bigfinite
Find out what your peers are saying about AWS Step Functions vs. Apache Airflow and other solutions. Updated: December 2024.
824,053 professionals have used our research since 2012.