SAP Signavio Process Manager and Apache Airflow are competing process management solutions. Apache Airflow appears to have an edge due to its robust integration and automation capabilities, beneficial for Python-oriented environments.
Features: SAP Signavio Process Manager is renowned for its collaborative process mapping, offering a workspace where global teams can engage and improve workflows together. The tool's modeling capabilities and version management ensure comprehensive process documentation. In contrast, Apache Airflow excels in orchestrating complex workflows through Directed Acyclic Graphs (DAGs), crucial for Python-based integrations, allowing seamless automation and workflow monitoring.
Room for Improvement: SAP Signavio Process Manager could improve by refining its interface to better accommodate complex workflows and integrating a document management system. Enhancements in predictive analytics and user license flexibility would also benefit adoption. Apache Airflow requires improved support for pipelined workflows, a more user-friendly interface, and better technical support. It lacks cyclic graph support and faces challenges in platform integration and scaling simplicity.
Ease of Deployment and Customer Service: Both SAP Signavio Process Manager and Apache Airflow support various cloud deployment options, including public and private clouds. SAP Signavio is commended for its proactive customer service, despite minor communication issues, providing timely assistance. Apache Airflow relies on community support due to its open-source nature, where support quality can vary, making it less reliable than SAP Signavio's service.
Pricing and ROI: SAP Signavio Process Manager offers a flexible pricing model, though it can be costly, particularly with SAP integration. Despite higher costs, organizations see ROI through enhanced process optimization and collaboration. Apache Airflow, as an open-source tool, provides a cost-effective entry point with expenses depending on deployment infrastructure, yielding substantial ROI in automation efficiency, though detailed ROI tracking remains uncommon due to its nature and diverse deployment scenarios.
There is enough documentation available, and the community support is good.
Forums and community resources like Stack Overflow are helpful.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
The solution is very scalable.
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.
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.
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.
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.”
The Signavio portfolio of web-based business transformation solutions helps companies to understand and optimize all of their business processes quickly and at scale, providing instant insights for informed decision-making. Signavio’s intuitive analysis, change management and execution solutions around process excellence include use cases like digital transformation, operational excellence and customer-centricity, placing them at the heart of global organizations.
Over 1 million users in more than 1,500 organizations worldwide rely on Signavio products to make processes part of their company’s DNA. Headquartered in Berlin, Germany, Signavio was founded in 2009 to address the need for a collaborative approach to process management.
Signavio was acquired by SAP in the first quarter of 2021. For more information, visit www.signavio.com
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