Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL.
N/A
Pega Platform
Score 8.5 out of 10
N/A
Pega Platform is a combined business process management and robotic process automation (RPA) platform with advanced workforce analytics from Pegasystems.
$0.45
one-time fee per case**
Pricing
Apache Airflow
Pega Platform
Editions & Modules
No answers on this topic
Low-code Factory Edition
$0.45
one-time fee per case**
Standard Edition
$0.80
one-time fee 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
—
**350,000 cases / year minimum. Additional cases available in blocks of 150,000.
More Pricing Information
Community Pulse
Apache Airflow
Pega Platform
Features
Apache Airflow
Pega Platform
Workload Automation
Comparison of Workload Automation features of Product A and Product B
Apache Airflow
8.7
12 Ratings
5% above category average
Pega Platform
-
Ratings
Multi-platform scheduling
9.312 Ratings
00 Ratings
Central monitoring
8.912 Ratings
00 Ratings
Logging
8.512 Ratings
00 Ratings
Alerts and notifications
9.312 Ratings
00 Ratings
Analysis and visualization
6.712 Ratings
00 Ratings
Application integration
9.412 Ratings
00 Ratings
Reporting & Analytics
Comparison of Reporting & Analytics features of Product A and Product B
Apache Airflow
-
Ratings
Pega Platform
5.3
63 Ratings
38% below category average
Dashboards
00 Ratings
4.062 Ratings
Standard reports
00 Ratings
6.062 Ratings
Custom reports
00 Ratings
6.061 Ratings
Process Engine
Comparison of Process Engine features of Product A and Product B
Apache Airflow
-
Ratings
Pega Platform
8.0
66 Ratings
4% below category average
Process designer
00 Ratings
8.965 Ratings
Process simulation
00 Ratings
7.857 Ratings
Business rules engine
00 Ratings
9.965 Ratings
SOA support
00 Ratings
7.251 Ratings
Process player
00 Ratings
7.048 Ratings
Support for modeling languages
00 Ratings
5.46 Ratings
Form builder
00 Ratings
9.059 Ratings
Model execution
00 Ratings
8.656 Ratings
Collaboration
Comparison of Collaboration features of Product A and Product B
Apache Airflow
-
Ratings
Pega Platform
9.0
50 Ratings
7% above category average
Social collaboration tools
00 Ratings
9.050 Ratings
Content Management Capabilties
Comparison of Content Management Capabilties features of Product A and Product B
Airflow is well-suited for data engineering pipelines, creating scheduled workflows, and working with various data sources. You can implement almost any kind of DAG for any use case using the different operators or enforce your operator using the Python operator with ease. The MLOps feature of Airflow can be enhanced to match MLFlow-like features, making Airflow the go-to solution for all workloads, from data science to data engineering.
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.
Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.
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.
UI/Dashboard can be updated to be customisable, and jobs summary in groups of errors/failures/success, instead of each job, so that a summary of errors can be used as a starting point for reviewing them.
Navigation - It's a bit dated. Could do with more modern web navigation UX. i.e. sidebars navigation instead of browser back/forward.
Again core functional reorg in terms of UX. Navigation can be improved for core functions as well, instead of discovery.
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
For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.
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.
Multiple DAGs can be orchestrated simultaneously at varying times, and runs can be reproduced or replicated with relative ease. Overall, utilizing Apache Airflow is easier to use than other solutions now on the market. It is simple to integrate in Apache Airflow, and the workflow can be monitored and scheduling can be done quickly using Apache Airflow. We advocate using this tool for automating the data pipeline or process.
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.
Impact Depends on number of workflows. If there are lot of workflows then it has a better usecase as the implementation is justified as it needs resources , dedicated VMs, Database that has a cost
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