AgilePoint and Apache Airflow are competing in workflow and process automation. AgilePoint is known for its comprehensive application development, while Apache Airflow excels in managing complex data workflows. Apache Airflow is preferred for its robust performance and orchestration capabilities.
Features: AgilePoint offers process management, extensive integration with tools like Microsoft and UiPath, and anonymous hosting options. Apache Airflow is sought for its UI in automation, Python integration, and the ability to monitor ETL processes on a single screen as well as its flexibility with DAG presentation.
Room for Improvement: AgilePoint could enhance its support for non-technical users and expand its integration capabilities with niche platforms. More extensive training resources would also be beneficial. Apache Airflow could benefit from simplifying its setup process and adding support for drag-and-drop interfaces. Enhanced visual workflow designers and less reliance on Python for configuration would also improve user experience for non-technical users.
Ease of Deployment and Customer Service: AgilePoint provides an easy cloud-based deployment model with rapid scalability and extensive support services. Apache Airflow requires more technical expertise due to its open-source nature but offers significant flexibility and active community support.
Pricing and ROI: AgilePoint has a structured pricing model ideal for enterprises aiming for fast ROI through efficient process management. Apache Airflow, being open-source, is cost-effective regarding licensing, but deployment and maintenance might increase upfront costs, with ROI primarily achieved through managing complex data workflows efficiently.
AgilePoint NX is a top-five low-code platform that empowers you to quickly build anything from simple eforms and workflows to complex, multi-tenant SaaS apps, IoT apps, and composite LOB systems without writing code and at a price almost any enterprise can afford.
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.”
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.
