ARIS BPA and Apache Airflow both operate within the realm of business process management and workflow automation, yet they serve differing needs. ARIS BPA leans towards a comprehensive process modeling and analysis framework while Apache Airflow is adept at workflow automation. Apache Airflow has the upper hand in automation capabilities but ARIS BPA excels in detailed process modeling.
Features: ARIS BPA focuses on process modeling and enterprise strategy alignment with features like extensive reporting, SAP integration, and a comprehensive modeling environment. Apache Airflow is centered around workflow automation and task scheduling, utilizing Python-based DAGs for integration with data science workflows and ease of customization.
Room for Improvement: ARIS BPA lacks a workflow engine for process execution, has limited tool integration, and is considered expensive. Apache Airflow faces limitations with cyclic workflows and real-time processing, has complex state-managed setup, and needs UI improvements.
Ease of Deployment and Customer Service: ARIS BPA supports On-premises, Private Cloud, and Hybrid Cloud deployments but suffers from complex integration and high setup costs. Apache Airflow is open-source, flexible in deployment, often cloud-based for scalability, and relies on community support or commercial options like Astronomer.
Pricing and ROI: ARIS BPA has high pricing with complex licensing but offers significant ROI when fully utilized. Apache Airflow, being open-source, has no initial costs though managed services may incur expenses, with ROI depending on automation savings.
Forums and community resources like Stack Overflow are helpful.
There is enough documentation available, and the community support is good.
The consultants are fine, however, reliance on single experts for modules can be risky.
The solution is very scalable.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
For user scalability, it is a matter of licenses, while functional scalability is supported and easy to implement.
I would rate the stability of the solution as ten out of ten.
Apache Airflow is stable and I have not experienced significant issues.
The stability of ARIS BPM is quite strong, rated eight out of ten.
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.
Software AG could improve this by making the database more open.
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.
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.
The maintenance capabilities of ARIS BPM and the strong underlying database are particularly valuable.
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.”
ARIS is the market-leading solution for professional business process management and modeling. Whether you want to document the "as-is" state of your operations for quality or certification reasons or design the "to-be" in terms of continuous improvement in your transformation program, ARIS is the best choice for establishing a single source of truth regarding all process excellence topics in your organization. It is for any organization looking to digitally transform their business, increase operational excellence and customer experience and ensure compliance in execution. ARIS helps you to make the most out of your processes with Process Mining, Risk & Compliance Management, RPA and much more.
What makes the difference?
ARIS is the market-leading solution for any organization and ideally suited to digitally transform the organization, increase operational excellence and customer experience and ensure compliance in execution.
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.
