Find out in this report how the two Business Process Management (BPM) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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.”
AWS Step Functions is widely utilized for constructing data management pipelines, such as data validation and database tasks. The system especially excels in parallel ETL job execution, managing complex microservices workflows, and integrating AWS services for smooth task automation and infrastructure orchestration.
Offering extensive control over historical events and parallelization, AWS Step Functions shines with its visual design capabilities, which enhance usability and pipeline troubleshooting. Users find it efficient for debugging and appreciate the graphical interface for a comprehensive system overview, making it easier to integrate with microservices. Its key functionalities include managing event grids and API integrations for optimized workflows.
What are the key features of AWS Step Functions?
What benefits should users look for in AWS Step Functions reviews?
In industries like finance, healthcare, and e-commerce, AWS Step Functions is employed to automate complex workflows, manage large-scale data processing tasks, and enable real-time data integration. Specifically, industries benefit from its ability to validate data, automate backups, and coordinate various microservices, ensuring robust and reliable operations. Companies look for better pricing, data limits, better IDE integration, and improved data transformation features. Enhanced visibility into executions and support for third-party tools are sought, along with seamless credentials access and more dynamic coding approaches.
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