Item: Apache Airflow
Rating: 9
Author: Verified User

Use Cases and Deployment Scope

We are using Apache Airflow for streamline the data pipelines, creating the workflow, Schedule the workflow as per the need, and also monitor the same, we are solving the problem of fetching the data from hive and then created the complete workflow and also we are using for automation as well.

Pros and Cons

Smart Automation
Highly Scalable
Complex Workflow
Easy Integration with other system

Documentation part
GUI can be improved
Reliability issues

Return on Investment

Overall positive impact using apache airflow
Easy to use
Easy to integrate which saves time

Alternatives Considered

Apache Spark, Apache Spark MLib and Qlik Analytics Platform

Overall using Apache Airflow is easy to use compare than other other tools available in the market, It is easy to integrate in apache airflow and the workflow can be monitored and scheduling can be done easily using apache airflow, recommend this tool for Automating the data pipeline or workflow.

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 Spark, Apache Spark MLib, Apache Spark Streaming

Likelihood to Recommend

Apache Airflow is best suited for the data engineers for creating the data workflows, and it is best suitable for the scheduling the workflow and also we can run the python codes as well using apache airflow, and it is suited for the situation where we need scalable solution. Monitoring can be done easily.

Apache Airflow for Automation and scheduling

Overall Satisfaction with Apache Airflow