Easy integration: Apache Airflow can easily be integrated with cloud platforms (Google, AWS, Azure, etc).Intuitive user interface: The Apache Airflow user interface enables you to visualize pipelines running in production, monitor progress, and also troubleshoot issues when needed.User friendly: Using Apache Airflow requires minimal python knowledge to get started.Some of the biggest advantages the solution offers include: There are many benefits to implementing Apache Airflow. 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.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.
#Apache airflow competitors code
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.The smart sensors are executed in bundles, and therefore consume fewer resources. Smart sensor: In Apache Airflow, tasks are executed sequentially.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).Īpache Airflow has many valuable key features.
The solution makes it possible for you to manage your data pipelines by authoring workflows as directed acyclic graphs (DAGs) of tasks.
Although Apache Airflow is generally dependable, it may occasionally encounter glitches that can disrupt production flows and batches." "UI can be improved with additional user-friendly features for non-programmers and for fewer coding practitioner requirements."Īpache 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. This necessitated modifying some configurations to initiate a restart of all Apache Airflow components. To resolve such situations, we had to manually reboot Apache Airflow since it doesn't provide an option to restart within the application. You have to build it into a Kubernetes container, which is not easy to maintain, and I find it to be very clunky." "The graphical user interface can be improved." "We have faced scenarios where Apache Airflow becomes non-responsive, leading to job failures. Else, we have to put a senior engineer to operate it." "Adding more automated components in Apache Airflow for basic things like exporting the data would be helpful." "The problem with Apache Airflow is that it is an open-source tool. They should make it simple for newcomers. "I would like to see some no-code capabilities and drag and drop abilities in Airflow." "For admins, there should be improved logging capabilities because Apache Airflow does have logging, but it's limited to some database data." "There is an area for improvement in onboarding new people. The number of operators and features I've used are mainly related to connectivity services and integrated services because I primarily work with GCP." "I found the following features very useful: DAG - Workload management and orchestration of tasks using." They also have a graphical view, so if you are not a programmer and you are just an administrator, you can easily track everything and see if everything is working or not." "Every feature in Apache Airflow is valuable. Everything is in Python, so it's not hard to understand. Additionally, the reattempt at failed jobs is useful." "Since the solution is programmatic, it allows users to define pipelines in code rather than drag and drop." "Development on Apache Airflow is really fast, and it's easy to use with the newer updates. "Designing processes and workflows is easier, and it assists in coordinating all of the different processes." "The best feature is the customization." "Since Apache works very well on Python, we can manage everything and create pipelines there." "The most valuable feature of Apache Airflow is creating and scheduling jobs.
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