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.
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.
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.
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.
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.