Rumor has it that with the rise of Apache Spark, Spark will replace Hadoop.
Well, let’s take a look. Apache Spark is an open-source processing engine that supports interactive quieries while Hadoop is an easy to scale, cost effective data storage. The truth is- Spark does not replace Hadoop, in fact, Hadoop and Spark complement one another.
Now you may wonder: how will Spark and Hadoop affect your big data strategy?
Watch this 8-minute video with Josh Klahr to understand:
- How Spark and Hadoop work together
- How Spark is different from other SQL on Hadoop Engines and what its advantages are
- What you should consider when evaluating SQL on Hadoop Engines
There is no one solution for all of your big data problems. To learn more about Hadoop and BI on Hadoop, check out the resources below.
- Guide: SQL on Hadoop Benchmark – The different performance of different SQL on Hadoop Engines.
- Blog: Why Spark and Hadoop are both here to stay – How roles differ for both Spark and Hadoop in the Big Data space.
- Tech Webinar: The Do’s and Don’ts of BI on Hadoop - Things that work and things that don’t when deploying BI on Hadoop.
Thank you for reading this blog. We hope this overview was valuable, if there are other questions you’d like us to address please feel free to comment below.
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