Item: Apache Airflow
Rating: 7
Author: Alok Pabalkar

Use Cases and Deployment Scope

Used Airflow for Analytics & Reporting

Pros and Cons

Reports
Sending Bulk Email/Notification
Processing from different data sources

Improve the GUI Control Panel
Provide more example and documentation
Improvement in debugging

Return on Investment

Impact Depends on number of workflows. If there are lot of workflows then it has a better usecase as the implementation is justified as it needs resources , dedicated VMs, Database that has a cost
Donot use it if you have very less usecases

digdag (https://www.digdag.io/)- Digdag is a very simple build, run, schedule, and monitor complex pipelines of tasks with a simple implementation and no configuration. Easy to write YAMLs

Airflow has a better community and widely adopted. Has a better UI and better documentation

Key Insights

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

Other Software Used

Apache Kafka, Redis™*, PostgreSQL

Likelihood to Recommend

Very well suited for building ETL, Automated report generation as the workflow steps can be well defined and debugging is minimal. It can also be used for sending bulk email/sms/push notifications.

But when more complex workflows have to be implemented where the response of a task can create multiple branches and there are multiple feedback loops, the tool can become tedious.

Apache Airflow for Startups

Overall Satisfaction with Apache Airflow