Workload Automation Blog

10 Troubling Excuses for Using Oozie with Hadoop Workflows

2 minute read
Basil Faruqui

Now is as good a time as any to think about what you’re going to do differently in 2018 to make it easier to keep up with the demands of big data. A great place to start is to look closely at the tools you’re using for working with Hadoop workflows. Let’s face it — if you’re using Oozie, you’re relying on older technology with limitations and inconsistences that can slow you down. Plus, there’s a much more effective alternative that enables you to automate big data workflows faster and easier — Control-M for Hadoop.

To validate our confidence in this product, we put Control-M to a test. We asked an independent company that specializes in big data to explore the functional differences between Oozie and Control-M for Hadoop. Spoiler alert: Control-M takes the lead across the board, as described in this summary based on their analysis.

“Oozier” isn’t easier

If you’ve been struggling with using Oozie with Hadoop workflows, or if you’re just starting a big data project, you’ll discover why these experts determined that Control-M provided a better, faster, and easier way for creating, testing, deploying and managing Hadoop-based workflows. Keep in mind that these testers came to this conclusion even though they had never used Control-M before but had extensive experience with Oozie.

  • After building a user-monitoring mobile application with Oozie and Control-M, they were able to develop workflows 40% faster with Control-M.
  • They also discovered very quickly how Control-M provided more security and included more features out of the box to avoid disrupting business activity and increase business value.

Read this summary for a side-by-side comparison. Specific testing included building workflows; scheduling, managing and updating jobs; conducting imports and file transfers; and evaluating security.

What excuses are holding you back from making a switch?

While some enterprises are familiar with Oozie, their teams may not realize all of the benefits of Control-M. For example, if you agree with the statements below, then go ahead and stick with Oozie. But if you don’t, then consider Control-M.

  1. The push to innovate is overrated – speed couldn’t possibly matter that much in developing workflows.
  2. Why even bother being concerned about scalability?
  3. Oozie may not meet most of my operational needs but at least it’s free.
  4. My team likes the extreme challenge of managing Hadoop workflows from multiple interfaces.
  5. Dealing with never-ending software bugs makes work exciting, even though it’s time-consuming and frustrating.
  6. Why leverage automation when I can spend countless hours writing scripts?
  7. Let someone else worry about file transfer security – It’s not my job.
  8. If the results of scheduling big data workflows are not accurate the first time, well, maybe they’ll be accurate later on.
  9. I’ve been using Oozie for many years. I don’t have the time to even think about switching to something that’s so much better.
  10. Digital business activity can wait. I’m too busy.

Get the facts

Want to learn more about the differences between Control-M and Oozie for managing Hadoop workflows?
Read the summary and see for yourself.
Access the white paper that compares the tools.

These postings are my own and do not necessarily represent BMC's position, strategies, or opinion.

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About the author

Basil Faruqui

Basil joined BMC in 2003 and has worked in several different technical and management roles within Control-M and Remedy product lines. He is currently working as a Principal Solutions Marketing manager for Control-M where his areas of focus include DevOps, big data and cloud. Basil has an MBA in Marketing and a BBA in Management Information Systems from the University of Houston. He has more than 15 years’ experience in technology that spans Software Development, Customer Support, Marketing, Business Planning and Knowledge Management.