Scalable Scheduling Framework and Orchestration tool
Updated May 30, 2025
Scalable Scheduling Framework and Orchestration tool
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Apache Airflow
We are using Apache Airflow as an orchestration tool in data engineering workflows in gaming product.
We are scheduling multiple jobs i.e hourly / daily / weekly / monthly.
We have a lot of requirement for dependent jobs i.e job1 should mandatory run before job2, and Apache Airflow does this work very swiftly, we are utilising multiple Apache Airflow integration with webhook and APIs. Additionally, we are doing a lot of jobs monitoring and SLA misses via Apache Airflow features
We are scheduling multiple jobs i.e hourly / daily / weekly / monthly.
We have a lot of requirement for dependent jobs i.e job1 should mandatory run before job2, and Apache Airflow does this work very swiftly, we are utilising multiple Apache Airflow integration with webhook and APIs. Additionally, we are doing a lot of jobs monitoring and SLA misses via Apache Airflow features
Pros
- Job scheduling
- Dependent job workflows
- Failure handling and rerun of workflows
Cons
- Better User Interface
- Good in job scheduling and dependency management between jobs
- Robust framework to monitor jobs and alert in case of failure and SLA misses
- Great integration with multiple open source tools
Open source
Easy to configure
Easy to learn
Robust and reliable
Easy to configure
Easy to learn
Robust and reliable
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
Comments
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