Pega Platform and Apache Airflow compete in the automation and workflow orchestration markets. Pega Platform appears more advantageous for enterprises with complex workflows due to its robust case management and decision-making capabilities, while Apache Airflow offers flexibility and scalability for tech-savvy teams with Python-based workflow automation.
Features: Pega Platform features robust case management, a comprehensive no-code environment, and robotic automation capabilities. Apache Airflow excels in Python-based workflow automation, offering flexibility through its configuration-driven approach and providing scalability ideal for data engineering tasks.
Room for Improvement: Pega Platform could improve in pricing, enhance cloud presence, and advance integration capabilities, specifically incorporating more AI and accessibility for smaller companies. Apache Airflow could enhance cyclic workflow support, dashboard capabilities, and simplify its integration process to better manage larger workflows.
Ease of Deployment and Customer Service: Pega Platform provides versatile deployment options, including on-premises, private, public, and hybrid cloud environments, but customer service can be slow due to dependencies. Apache Airflow is primarily deployed in public and on-premise clouds, requiring external support for large-scale deployments, with varying dynamics in customer support compared to Pega.
Pricing and ROI: Pega Platform, with its enterprise-level features, entails higher licensing costs based on user count and implementation scale, offering substantial ROI in complex environments when fully utilized. Apache Airflow, being open-source and free, provides a cost-effective solution, though support costs could accrue with commercial distributions like Astronomer.
I estimate that projects take days rather than weeks when using Pega Platform compared to traditional coding.
Pega Platform has positively impacted my organization, as they were using different technology before and have seen tremendous success and return on investment, so they are very happy.
Forums and community resources like Stack Overflow are helpful.
There is enough documentation available, and the community support is good.
The technical support from Pega is very low, rating a one or two out of ten.
I never needed support from the platform standpoint, but if additional features are required, we have regular meetings with the product team for feedback.
Pega's technical support team is very helpful.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
The solution is very scalable.
Currently, big banking providers and insurance providers, even the members for healthcare payers, are using more than millions of operations on a daily or weekly basis.
I would rate the stability of the solution as ten out of ten.
I would rate its stability at nine out of ten.
Apache Airflow is stable and I have not experienced significant issues.
It is not suitable for real-time ETL tasks.
There is no dashboard for us to check all the Directed Acyclic Graphs (DAGs); a dashboard would help us analyze the work better.
If we desire to add custom messengers or a rest API, those options are unavailable.
For customer interactions, while the Pega Platform's AI-based decisioning and predictive analytics are great, the Process AI is not very popular yet, as it works on process data rather than customer data.
There are always areas for improvement, which they are addressing in every part of the patch releases.
Pega introduced Constellation, which allows a user to build a more engaging visual experience.
I prefer using the open-source version rather than the enterprise version, which helps manage costs.
It is a sub-feature and not an individual purchase.
Apache Airflow is a community-based platform and is not a licensed product.
From a licensing perspective, it is higher than the competition.
The pricing is expensive, and this is an issue.
Pega is priced higher than open-source options like Flowable but is suitable for large-scale industries like banking and insurance.
Reliability is good, and when integrated with Kubernetes, it performs better compared to on-premises environments.
Apache Airflow is an open-source platform that allows easy integration with AWS, Azure, and Google Cloud Platform.
We can create notifications for successful or failed tasks, providing a practical way to monitor our workflows.
Pega Platform has positively impacted my organization by providing faster application development than traditional methods.
The best feature is case management, which is so automated and does most of the things out of the box without requiring a lot of customizations.
Pega Platform is excellent for enterprise-level solutions with integrations to entire systems, including case management, service orchestration, CRM, decision-making capabilities, digital process automation, and AI-driven functionalities.
| Product | Market Share (%) |
|---|---|
| Apache Airflow | 3.5% |
| Pega Platform | 3.9% |
| Other | 92.6% |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 3 |
| Large Enterprise | 24 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 15 |
| Large Enterprise | 69 |
Apache Airflow is an open-source workflow management system (WMS) that is primarily used to programmatically author, orchestrate, schedule, and monitor data pipelines as well as workflows. The solution makes it possible for you to manage your data pipelines by authoring workflows as directed acyclic graphs (DAGs) of tasks. By using Apache Airflow, you can orchestrate data pipelines over object stores and data warehouses, run workflows that are not data-related, and can also create and manage scripted data pipelines as code (Python).
Apache Airflow Features
Apache Airflow has many valuable key features. Some of the most useful ones include:
Apache Airflow Benefits
There are many benefits to implementing Apache Airflow. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the Apache Airflow solution.
A Senior Solutions Architect/Software Architect says, “The product integrates well with other pipelines and solutions. The ease of building different processes is very valuable to us. The difference between Kafka and Airflow, is that it's better for dealing with the specific flows that we want to do some transformation. It's very easy to create flows.”
An Assistant Manager at a comms service provider mentions, “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.”
A Senior Software Engineer at a pharma/biotech company comments that he likes Apache Airflow because it is “Feature rich, open-source, and good for building data pipelines.”
Pega Platform provides flexible business process management with a focus on rapid application development and automation through a low-code approach, enhancing efficiency across sectors.
Pega Platform is renowned for its ability to streamline operations with robust automation features, including robotic process automation and decision-making capabilities. Its intuitive interface and workflow management contribute to a reputation for enhancing business processes. Although users face challenges with integration limitations and high licensing costs, they benefit from rapid deployment and efficient process adaptations. The unified architecture reduces complexity, while case management and integration services support digital transformations in sectors such as banking, insurance, and healthcare.
What are the key features of Pega Platform?
What benefits and ROI should users expect?
In industries like insurance, banking, healthcare, and government, Pega Platform is implemented to automate diverse workflows, supporting initiatives from claims processing to customer onboarding. Enterprises use Pega for case management and digital transformations, valuing its out-of-the-box integrations and real-time reporting capabilities to boost operational automation and enhance customer experiences.
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.
