Apache Airflow vs. IBM Workload Automation

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Airflow
Score 8.4 out of 10
N/A
Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s Incubator Program 2016 and announced as Top-Level Apache Project in 2019. It is used as a data orchestration solution, with over 140 integrations and community support.N/A
IBM Workload Automation
Score 6.9 out of 10
N/A
IBM Workload Automation (IBM Workload Scheduler, formerly Tivoli Workload Scheduler is IBM's IT workload automation offering.N/A
Pricing
Apache AirflowIBM Workload Automation
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache AirflowIBM Workload Automation
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache AirflowIBM Workload Automation
Considered Both Products
Apache Airflow
Chose Apache Airflow
Much easy to deploy Apache Airflow as opposed to other products, with flexible deployment options as well as flexible integration with other tools and platforms.
IBM Workload Automation

No answer on this topic

Top Pros
Top Cons

No answers on this topic

Features
Apache AirflowIBM Workload Automation
Workload Automation
Comparison of Workload Automation features of Product A and Product B
Apache Airflow
8.2
9 Ratings
0% above category average
IBM Workload Automation
-
Ratings
Multi-platform scheduling8.89 Ratings00 Ratings
Central monitoring8.49 Ratings00 Ratings
Logging8.19 Ratings00 Ratings
Alerts and notifications7.99 Ratings00 Ratings
Analysis and visualization7.99 Ratings00 Ratings
Application integration8.49 Ratings00 Ratings
Best Alternatives
Apache AirflowIBM Workload Automation
Small Businesses

No answers on this topic

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Medium-sized Companies
ActiveBatch Workload Automation
ActiveBatch Workload Automation
Score 8.6 out of 10
ActiveBatch Workload Automation
ActiveBatch Workload Automation
Score 8.6 out of 10
Enterprises
Redwood RunMyJobs
Redwood RunMyJobs
Score 9.4 out of 10
Redwood RunMyJobs
Redwood RunMyJobs
Score 9.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache AirflowIBM Workload Automation
Likelihood to Recommend
7.9
(9 ratings)
-
(0 ratings)
User Testimonials
Apache AirflowIBM Workload Automation
Likelihood to Recommend
Apache
For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.
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IBM
No answers on this topic
Pros
Apache
  • In charge of the ETL processes.
  • As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.
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IBM
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Cons
Apache
  • they should bring in some time based scheduling too not only event based
  • they do not store the metadata due to which we are not able to analyze the workflows
  • they only support python as of now for scripted pipeline writing
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IBM
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Alternatives Considered
Apache
There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.
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IBM
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Return on Investment
Apache
  • A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
  • Allowed us to implement complex data pipelines easily and at a relatively low cost
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IBM
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ScreenShots