Apache Airflow software
June 21, 2022
Apache Airflow software
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Apache Airflow
Apache Airflow is used for the scheduling and orchestration of data pipelines or workflows. Orchestration of data pipelines refers to the sequencing, coordination, scheduling, and managing of complex data pipelines from diverse sources. It is also helpful when your data pipelines change slowly (days or weeks – not hours or minutes), are related to a specific time interval, or are pre-scheduled.
- Scheduling of data pipelines or workflows.
- Orchestration of data pipelines or workflows.
- Not intuitive for new users.
- Setting up Airflow architecture for production is NOT easy.
- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc).
- For ETL pipelines that extract batch data from multiple sources, and run Spark jobs or other data transformations.
- It also helps to generate report automatically.
There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.
Do you think Apache Airflow delivers good value for the price?
Yes
Are you happy with Apache Airflow's feature set?
Yes
Did Apache Airflow live up to sales and marketing promises?
Yes
Did implementation of Apache Airflow go as expected?
Yes
Would you buy Apache Airflow again?
Yes