Apache Airflow vs. Striim

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

Below samples are the well suited use cases; - Change data capture feature seamlessly works on popular RDMS. You can make enrichments on several data sources within the same Striim application. - You can install stand alone agents and start streaming log files to Striim servers. This is mainly useful for security operations or audit trail use cases.

Incentivized

• In charge of the ETL processes.
• As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.

Incentivized

• GoldenGate Trail reader which iss faster than Oracle CDC. It does not used logminer, hence there is no load on source Oracle database.
• Easy installation and upgrade in 5 minutes
• Support is very good. Fast and user friendly.

• they should bring in some time based scheduling too not only event based
• they do not store the metadata due to which we are not able to analyze the workflows
• they only support python as of now for scripted pipeline writing

Incentivized

• License a bit expensive

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.

Incentivized

Faster, checkpointing better. CDC works well. The loading is faster. Easy upgrade and installation. Uses less resource.

• A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
• Allowed us to implement complex data pipelines easily and at a relatively low cost

Incentivized

• We got the license at a discount price