Apache Airflow vs. OpenText Operations Orchestration

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

The products are being paired by the company with different software to specifically fit multiple scenarios. As a standalone platform, it can answer any task with its build-in content or the ability to create your own content and solution.

• 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.

Incentivized

• Allows for the quick disconnection of accounts that break our terms of service
• Seamless integration with our billing system
• Has the ability to house all member/client account information in one single location

Incentivized

• 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

Incentivized

• The product build in portal need to be more flexible

Easy to learn Easy to use Robust workflow orchestration framework Good in dependent job management

Incentivized

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.

Incentivized

Most product works well enough, but none of them combine the non-agent/client approach to automation with an easy to develop mechanism (the drag&drop development approach) This alone put this solution on top of our preferred implantation product list

• 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

Incentivized

• If time is money, the time saved by using this all-in-one product has certainly saved time AND money.

Incentivized