Apache Airflow vs. CA Workload Automation

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.

Incentivized

If batch jobs are heavily used then this product is highly recommended since it maintains dependencies between jobs, notifies if there are any failures, and puts the next batches on hold if previous dependent jobs fails.

Incentivized

• Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
• Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
• Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.

Incentivized

• Workload can be scheduled across different Platforms.
• Support for Hadoop. Integration with Informatica Dataware house application.
• The latest version has a web interface which is very impressive.
• Low overheads from administration standpoint.

Incentivized

• A local "dry run" or IDE plugin that can validate and simulate DAG execution without needing a full environment.
• Better feedback on DAG parse errors in the UI or CLI.
• Navigating large DAGs with hundreds of tasks can be slow and hard to understand visually.

Incentivized

• Even though the CA Workload Automation GUI is simple and easy to use, it looks outdated and has limited features such as customizing dashboards and saving particular user settings.
• CA Workload Automation lacks performance and is often slow to edit jobs or to refresh screens and sometimes requires admin to restart service agents for background processes.
• I would like to see CA Workload Automation in one screen with all the information the user wants to see and have this customized and saved for every user. Rather than having to build a view and search criteria for every new job that is added.
• I would like a feature or configuration that you can setup different types of notifications for job failures such as text message with different levels of severity.

Incentivized

For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.

Incentivized

Very happy!

Incentivized

It would be great if customer chat experience is also readily available.

Incentivized

Apache Airflow is suited for a much wider set of use cases compared to Databricks. You can run it anywhere, and there is also no vendor lock-in. With Airflow, we can utilize almost any compute engine. Same thing we want to do with Databricks. There might be some level of difficulty based on the support.

Incentivized

CA Workload Automation stacks up very well compared to Cisco/Tidal, BMC and is far superior to crontab. CA Workload Automation has easy initial setup, efficient job management and scheduling, supports multiple applications and environments and improves business critical needs including SLA, increasing productivity while decreasing processing workload times and failures. CA Workload Automation also integrates well with Automation Change Control Expert or ACCE which is a nice migration tool to have if you're managing jobs in the thousands.

Incentivized

• Most of the ETL processes were automated, cutting down on human labor.
• Apache Airflow's user interface (UI) was very informative and straightforward.
• Since ETL processes were providing data via airflow, we were able to gain a deeper comprehension of the data at hand.

Incentivized

• Positively affected in resolving issues through alerts during peak traffic.
• Monitoring directly help during Thanksgiving and Black Friday traffic.
• Reporting helped in explanation of issues to higher management.

Incentivized