Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s Incubator Program 2016 and announced as Top-Level Apache Project in 2019. It is used as a data orchestration solution, with over 140 integrations and community support.
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Pega Platform
Score 5.7 out of 10
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Pega Platform is a combined business process management and robotic process automation (RPA) platform with advanced workforce analytics from Pegasystems.
$35
per month per user* (or $0.45 per case**)
Pricing
Apache Airflow
Pega Platform
Editions & Modules
No answers on this topic
Low-code Factory Edition
$35
per month per user* (or $0.45 per case**)
Standard Edition
$90
per month per user* (or $0.80 per case**)
Enterprise Edition
Custom Quote
Offerings
Pricing Offerings
Apache Airflow
Pega Platform
Free Trial
No
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
*500 named user minimum. Additional users available in blocks of 100. Billed annually. Based on a 3-year term.
**350,000 cases / year minimum. Additional cases available in blocks of 150,000.
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.
Pega Platform has introduced the low code feature, using app studio seasonal and professional developer can develop application easily and quickly. The initial application can be build by Business analyst and product owner who has less knowledge of Pega Platform, further application can be enhanced/extended by professional developer. We can develop end to end application and promote to higher environment. Easily we can perform parallel development using branch.
Quick development time. Much of the Pega "rules" are easy to configure and implement.
Visually friendly and modern. Much of the UI/UX elements in the system are continuously supported and updated, giving a nice feel to the apps.
Many of the configurations and rules Pega gives to the developers can also be delegated to business users. The organization and structure of the client's business can easily be adapted in the Pega platform.
Pegasystems has continued to demonstrate a strong partnership with our organization and investment in their product that aligns with our overall vision and need. Pegasystems has engaged us at every level, with the assistance of minor defects to the overall roadmap planning and alignment of our goals
Pega Platform is enhancing its product and launching new features day by day which help to achieve customers needs. If I talk about the earlier version of Pega Platform (i.e. pega v5 and 6.3) there were many numbers of limitations in Pega Platform and if we need to do some customization then needed to write custom java and jave scripts to achieve the functionally. Now I can say Pega Platform is running with market trends and demand. Pega Platform is giving all the options which support the current technologies like decisioning capabilities, real time processing, mashup, process fabrics etc..
It’s very slow sometimes, but that may be our servers. Also the Knowledge Library needs some work - again, not sure if it’s our setup or what- but I’m unable to search the body of an article for content, so I have to be very intentional with tagging, but it’s not ideal.
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.
We did evaluate multiple products offerings with Pega Platform capabilities and observed that Pega PRPC rules engine and case management capabilities are better over so many BPM Tools. We also conducted a detailed study with developers to identify the best products out of Suite of BPM products. It's observed that Rules engines integration is very streamlined with forms in Pega whereas other tools multiple have powerful data model capabilities but lacks the ease of creating business rules.
For one of the applications we worked on, we were able to reduce the processing time on a case from 2 days to 20 minutes by utilizing Pega
We were able to resolve the issue of the routing of cases to users based on a specific algorithm by use of Pega
Pega case management feature was extensively used in one of the application to establish a parent-child relationship which was very helpful for all the business users
