Pega Platform and Apache Airflow cater to business process management and workflow orchestration, respectively. Pega Platform often emerges as a preferred choice for enterprise solutions due to its comprehensive feature set, while organizations with a primary focus on data engineering may find Apache Airflow’s open-source flexibility appealing.
Features: Pega Platform stands out for business process management, case management, and low-code development, offering rapid prototyping and deployment. It excels with robust integrations, supporting complex enterprise requirements. Apache Airflow specializes in workflow orchestration, particularly for data engineering tasks, ensuring flexible and easy setup in Python environments. Its open-source nature allows adaptive management of data processing pipelines.
Room for Improvement: Pega Platform users suggest improvements in cloud presence, pricing, and upgrade complexity. Enhancements in automation and better documentation are needed, along with expanded integration capabilities. Apache Airflow users look for improved user interface aesthetics and documentation, alongside support for more programming platforms. Real-time capabilities and a more comprehensive integration feature set are also areas for development.
Ease of Deployment and Customer Service: Pega Platform supports deployment across on-premises, cloud, and hybrid systems, benefitting large enterprises, yet some users face challenges with service response times and deployment complexities. Apache Airflow offers flexibility in deployment across various environments, but user frustration with support services and customization options points to a need for better technical assistance and documentation.
Pricing and ROI: Pega Platform is priced higher due to its feature-rich enterprise capabilities, with varied licensing models that can be prohibitive for smaller businesses, but offers substantial ROI through business process enhancements. Apache Airflow provides a low-cost alternative with no licensing fees, appealing to budget-conscious operations focused on data orchestration without extensive financial commitments.
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.
The solution is very scalable.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
I would rate the stability of the solution as ten 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.
Pega introduced Constellation, which allows a user to build a more engaging visual experience.
My learning curve in robotics has been challenging.
I prefer using the open-source version rather than the enterprise version, which helps manage costs.
Apache Airflow is a community-based platform and is not a licensed product.
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.
Apache Airflow is an open-source platform that allows easy integration with AWS, Azure, and Google Cloud Platform.
Reliability is good, and when integrated with Kubernetes, it performs better compared to on-premises environments.
Management capabilities such as dashboards.
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.
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 facilitates business process management, case management, and workflow automation for industries like banking, insurance, and healthcare. It supports digital transformation and customer service enhancements with its low-code capabilities and seamless integrations.
Pega Platform enables users to create efficient systems for case management, financial operations, and digital transformations. It provides tools for client onboarding, quoting, claims processing, customer experience improvements, and content management. Pega's low-code approach allows for the automation of complex processes, making it suitable for enterprises looking for adaptability and rapid deployment. While it offers strong real-time analytics and decision automation, users acknowledge challenges in user interface, integration, and performance aspects. High costs and a learning curve need attention, and enhancements in AI features and cloud services are desired.
What are the key features of Pega Platform?In banking, Pega Platform automates loan processing, accelerates customer onboarding, and manages compliance. Insurance companies benefit from streamlined claims processing and policy management. Healthcare sectors use the platform for patient engagement and care coordination, enabling organizations to adapt quickly to changing industry requirements.
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