"The initial setup was straightforward and it does not take long to complete."
"The best part of Airflow is its direct support for Python, especially because Python is so important for data science, engineering, and design. This makes the programmatic aspect of our work easy for us, and it means we can automate a lot."
"I like the UI rework, it's much easier."
"We have been quite satisfied with the stability of the solution."
"The reason we went with Airflow is its DAG presentation, that shows the relationships among everything. It's more of a configuration-driven workflow."
"I found the following features very useful: DAG - Workload management and orchestration of tasks using."
"The product integrates well with other pipelines and solutions."
"The stability of the product is very good."
"The dashboard is connected into the BPM flow that could be improved."
"Technical support is an area that needs improvement."
"The scalability of the solution itself is not as we expected. Being on the cloud, it should be easy to scale, however, it's not."
"One specific feature that is missing from Airflow is that the steps of your workflow are not pipelined, meaning the stageless steps of any workflow. Not every workflow can be implemented within Airflow."
"I would like to see it more friendly for other use cases."
"We're currently using version 1.10, but I understand that there's a lot of improvements in version 2. In the earlier version that we're using, we sometimes have problems with maintenance complexity. Actually using Airflow is okay, but maintaining it has been difficult."
"UI can be improved with additional user-friendly features for non-programmers and for fewer coding practitioner requirements."
"Integrating with or interfacing with other tools like data management tools would be very helpful."
Airflow is a platform to programmatically author, schedule and monitor workflows.
Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.
When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.
Apache Airflow is ranked 8th in Business Process Management (BPM) with 7 reviews while OpenText ProVision is ranked 32nd in Business Process Management (BPM) with 1 review. Apache Airflow is rated 7.8, while OpenText ProVision is rated 7.0. The top reviewer of Apache Airflow writes "Helps us maintain a clear separation of our functional logic from our operational logic". On the other hand, the top reviewer of OpenText ProVision writes "Stable with okay pricing but needs better integration capabilities". Apache Airflow is most compared with Camunda Platform, Amazon Step Functions, IBM BPM, IBM Business Automation Workflow and Informatica Cloud Api and App Integration, whereas OpenText ProVision is most compared with ARIS BPA, Visio, Sparx Systems Enterprise Architect and Bonita.
See our list of best Business Process Management (BPM) vendors.
We monitor all Business Process Management (BPM) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.