Apache Airflow and OpenText AppWorks compete in workflow automation. Apache Airflow has the upper hand in flexibility and community support, while OpenText AppWorks excels in rapid low-code development.
Features: Apache Airflow is appreciated for its flexibility, Python integration, and support from a large community, making it ideal for complex workflows. It features configuration-driven workflows and integrates well with other tools. OpenText AppWorks is valued for its rapid low-code development capabilities and strong integration features, especially in business process management. It automates business processes and offers scalability as key differentiators.
Room for Improvement: Apache Airflow could enhance its UI, increase out-of-the-box features, and improve support for cyclical workflows. Better documentation, real-time job processing, and more integration options are needed. OpenText AppWorks requires improvements in its UI and mobile compatibility. Enhancing archival functionality and integration models would be beneficial. Both have room to improve integration and user-friendliness.
Ease of Deployment and Customer Service: Apache Airflow is versatile in deployment across various cloud environments and benefits from community support, though official support is limited. OpenText AppWorks offers flexibility in hybrid cloud setups and generally satisfactory customer service, with room for improvements to further enhance usability.
Pricing and ROI: Apache Airflow is cost-effective as an open-source solution, resulting in significant ROI due to low licensing costs, with expenses primarily involving infrastructure. OpenText AppWorks is more costly, with pricing based on user count and licensing models, offering comprehensive functionalities that justify the investment when aligned with business needs.
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.”
OpenText Appworks. AppWorks is OpenText's Enterprise Application Development and Management platform. It allows you to quickly and easily build purpose-specific apps for the enterprise using the web technologies such as HTML5, CSS3 and JavaScript. These apps can connect to the OpenText EIM Suite using RESTful API.
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.
