"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 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."
"The initial setup was straightforward and it does not take long to complete."
"The best part of Pega, for me, is that they let you reuse a lot of the aspects in the product."
"The most valuable feature is the situational layer cake."
"The solution is operating well overall."
"It is quite configurable, which is the most exciting feature. We can easily configure it as per our needs."
"It's a good tool for workflow automation."
"The most valuable feature is flexibility, as we can configure it to best suit our requirements."
"Pricing is a little on the high side."
"The initial setup is pretty straightforward."
"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."
"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."
"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."
"Sometimes when we are patching some data from the database, we are getting added as a timeout."
"We have experienced a few technical challenges, particularly triggering the workflow through file drops and accessing files."
"The main problem with Pega is that it is quite complex, so it is very difficult for the developer to learn."
"They need to support the solution better, at this time the company does not have enough support."
"Compared to other BPM products, the interface is somewhat complex, so the usability could be improved."
"Reporting is not so clear and not so great. We really struggle to get the right reporting. When we need reporting based on the content of the tickets, we are not able to get it. The MIS reporting is not great. That's one of the reasons why we are switching to ServiceNow. Its compatibility with the higher versions of Internet Explorer should be improved. It really works well in Mozilla Firefox or any other browser, but when it comes to Microsoft Edge or Internet Explorer, sometimes, the layout gets disturbed. The positioning of the buttons changes, and there is some distortion in the layout. I am not sure whether it is our configuration problem or Pega's, but when it is working in Mozilla Firefox, it should also work in Microsoft Edge or Internet Explorer."
"It should have integration with non-relational databases. A lot of databases are non-relational, and as a company, we are planning to move to NoSQL or open-source databases. It would be good if we are able to install and use Pega on a NoSQL database. They can also try to tailor or organize the company a bit differently and go more towards the microservice concept. I would like Pega to develop machine learning and intelligent AI algorithms. They have a good foundation in terms of the model and the stuff that we are using for some customers, and it will be good to onboard as many machine learning algorithms as possible."
"The local development approach is good in Pega, however, cost-wise, it's getting expensive. That needs to be addressed."
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.
Pega BPM helps you simplify and automate your operations so that you can reduce costs and improve business agility. Pega's unique Build For Change technology delivers repeatable solutions that can be efficiently reused and tailored to meet the requirements of diverse customers, product lines, channels, and geographies.
Apache Airflow is ranked 8th in Business Process Management (BPM) with 7 reviews while Pega BPM is ranked 4th in Business Process Management (BPM) with 18 reviews. Apache Airflow is rated 7.8, while Pega BPM is rated 8.2. 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 Pega BPM writes "Good case management and BPM workflow with easy cloud implementation". Apache Airflow is most compared with Camunda Platform, Amazon Step Functions, IBM BPM, IBM Business Automation Workflow and ProcessMaker, whereas Pega BPM is most compared with Camunda Platform, ServiceNow, Appian, IBM BPM and Microsoft PowerApps. See our Apache Airflow vs. Pega BPM report.
See our list of best Business Process Management (BPM) vendors.
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