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:
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Smart sensor: In Apache Airflow, tasks are executed sequentially. The smart sensors are executed in bundles, and therefore consume fewer resources.
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Dockerfile: By using Apache Airflow’s dockerfile feature, you can run your business’s Airflow code without having to document and automate the process of running Airflow on a server.
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Scalability: Because Apache Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers, you can easily scale it.
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Plug-and-play operators: With Apache Airflow, you can choose from several plug-and-play operators that are ready to execute your tasks on many third-party services.
Apache Airflow Benefits
There are many benefits to implementing Apache Airflow. Some of the biggest advantages the solution offers include:
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User friendly: Using Apache Airflow requires minimal python knowledge to get started.
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Intuitive user interface: The Apache Airflow user interface enables you to visualize pipelines running in production, monitor progress, and also troubleshoot issues when needed.
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Easy integration: Apache Airflow can easily be integrated with cloud platforms (Google, AWS, Azure, etc).
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Visual DAGs: Apache Airflow’s visual DAGs provide data lineage, which facilitates debugging of data flows and also aids in auditing and data governance.
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Flexibility: Apache Airflow provides you with several ways to make DAG objects more flexible. At runtime, a context variable is passed to each workflow execution, which is quickly incorporated into an SQL statement that includes the run ID, execution date, and last and next run times.
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Multiple deployment options: With Apache Airflow, you have several options for deployment, including self-service, open source, or a managed service.
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Several data source connections: Apache Airflow can connect to a variety of data sources, including APIs, databases, data warehouses, and more.
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.”
webMethods Integration Server is widely considered to be the best integration server available in the marketplace today. The solution can help users integrate everything and anything.
webMethods Integration Server allows organizations to display and integrate existing and new business activities. The solution offers components that help users create, test, and install new services. webMethods Integration Server can automate, organize, and construct various gathered services and traditional legacy systems into productive value-added processes. webMethods Integration Server works as a secure platform for distributing and running services. The solution obtains and translates user requests, recognizes and records the requested service, translates and moves the data in the necessary format, receives the information back, and returns the information to the user in the appropriate original format. webMethods is the primary solution used by enterprise organizations for integrating functional coordination with application servers, custom applications, and databases. webMethods makes it easy for enterprise organizations to share electronic documents seamlessly.
Users have several options to audit webMethods Integration Server processes using some of the component metrics below:
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Adapters: Using the SOA extension for webMethods, users can easily monitor the performance of every adapter users have deployed. Available metrics include Adapter Services, Adapter Connection Pools, and Adapter Notifications nodes.
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Business Processes: A business process is a process that uses a specific set of rules to perform tasks in a prescribed order. Many business processes depend on the successful integration of numerous systems, involving many people in varying roles. With the SOA extension for webMethods, users can easily monitor that workflow, ensuring that processes are being performed as defined.
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Java Services: This includes services created in Java or in languages coordinated with Java.
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WebServices: This includes services regarding webserver endpoints and performance.
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XSLT Services: This service will allow users to transform XML data into other formats and includes the transformation to other services.
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Thread Pools: This metric uses threads to conduct services, gather documents from the webMethods Broker, and initiate triggers. Documents can be published locally on the server or to the broker that will send the document out. A JMS trigger receives inbound messages and then processes those messages accordingly.
Reviews from Real Users:
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