Robust Pipelines: Airflow pipelines are basic and explicit.Furthermore, it allows users to resume work from where they left off without having to restart the entire workflow. It allows users to create Machine Learning models, manage infrastructure, and transmit data, with no limitations on pipeline scope. Easy to Use: Anyone who is familiar with the Python programming language can easily set up an Airflow Data Pipeline.Let’s take a glance at the amazing features Airflow offers that makes it stand out among other solutions: Key Features of Apache AirflowĪpache Airflow is used by many firms, including Slack, Robinhood, Freetrade, 9GAG, Square, Walmart, and others. It is perfect for orchestrating complex Business Logic since it is distributed, scalable, and adaptive. It integrates with many data sources and may notify users through email or Slack when a job is finished or fails. Airflow’s powerful User Interface makes visualizing pipelines in production, tracking progress, and resolving issues a breeze. Users may design workflows as DAGs (Directed Acyclic Graphs) of tasks using Airflow. This functionality may also be used to recompute any dataset after making changes to the code. It’s also used to train Machine Learning models, provide notifications, track systems, and power numerous API operations. Airflow also has a backfilling feature that enables users to simply reprocess prior data. Its usefulness, however, does not end there. Airflow has become one of the most powerful open source Data Pipeline solutions available in the market.Īirflow was built to be a highly adaptable task scheduler. Your Data Pipelines’ dependencies, progress, logs, code, trigger tasks, and success status can all be viewed instantly. It’s one of Data Engineers’ most dependable technologies for orchestrating operations or Pipelines. Airflow Alternatives: AWS Step FunctionsĪpache Airflow is a workflow authoring, scheduling, and monitoring open-source tool.Top 7 Apache Airflow Alternatives in 2022.Before you jump to the Airflow Alternatives, let’s discuss what is Airflow, its key features, and some of its shortcomings that led you to this page. You can try out any or all and select the best according to your business requirements. To help you with the above challenges, this article lists down the best Airflow Alternatives along with their key features. With that stated, as the data environment evolves, Airflow frequently encounters challenges in the areas of testing, non-scheduled processes, parameterization, data transfer, and storage abstraction. Thousands of firms use Airflow to manage their Data Pipelines, and you’d be challenged to find a prominent corporation that doesn’t employ it in some way. You can also examine logs and track the progress of each task. Apache Airflow has a user interface that makes it simple to see how data flows through the pipeline. It leverages DAGs(Directed Acyclic Graph) to schedule jobs across several servers or nodes. Apache Airflow is a workflow orchestration platform for orchestrating distributed applications.
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