"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."
"I like the UI rework, it's much easier."
"We have been quite satisfied with the stability of the solution."
"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."
"The initial setup was straightforward and it does not take long to complete."
"The product integrates well with other pipelines and solutions."
"Provides a valuable BPMN feature."
"We found the technical support to be helpful."
"The dashboard is connected into the BPM flow that could be improved."
"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."
"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."
"Technical support is an area that needs improvement."
"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."
"The price could be more competitive."
"It would be nice to have a Spanish user interface available to us."
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 iGrafx is ranked 17th in Business Process Management (BPM) with 2 reviews. Apache Airflow is rated 7.8, while iGrafx is rated 8.6. 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 iGrafx writes "Easy to set up with useful features and good stability". 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 iGrafx is most compared with Visio, ARIS BPA, Visual Paradigm, SAP Signavio Process Manager and Bizagi. See our Apache Airflow vs. iGrafx report.
See our list of best Business Process Management (BPM) vendors.
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