Apache Airflow vs. TimeXtender

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

TimeXtender has worked really well with our customers who have different data sources using complex data types in large quantities requiring a DW-like solution that can consolidate all data sources at one-HUB. TimeXtender does this well, and provides automation capabilities, the ability to easily handle slowly changing dimensions, handing data lineage and data security very well. TimeXtender has the ability to be very customizable, allowing the HUB to grow as your business does. TimeXtender's customer support team is super helpful and will work with you throughout your implementation to make sure you reach success with the product. The ROI for timeXtender versus competing products (there aren't many that do what timeXtender does) shows the investment to be worthwhile for the majority of organizations in today's data-rich corporate world.

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

• It has the ability to create one dynamic 'DW' or source of truth, consolidating all data sources in one HUB.
• Ease of use, with a great UI that is easy to learn and adapt to.
• Ease/speed of complex implementation.

Incentivized

• 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

• Product Marketing: As implementers and resellers of this technology, we loved it. But, convincing clients who had not previously heard of TX/Discovery Hub was more difficult than it could have been if the company had a larger marketing force behind it.
• Relatively New to Market: it creates a learning curve for early implementers.
• More information should be published on timeXtender's website about product lines, including testimonials.

Incentivized

Easy to learn Easy to use Robust workflow orchestration framework Good in dependent job management

Incentivized

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

For our clients, timeXtender was a much better solution. It offered a more cost-effective solution, easier integration, and better customer support for our complex client needs. The timeXtender team worked with us throughout the process to make sure we could create a success story that was repeatable for our clients, and they proved great partners.

Incentivized

• 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