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Introduction

The emergence of Spark and machine-learning cloud services have prompted the question of whether Hadoop is essential. The real issue is how broad-based the implementation will be, and what the requirements are for data governance.

Highlights

  • The note makes the case for where Hadoop and specialized cloud-based Spark and machine-learning services fit in.

Features and Benefits

  • Provides guidance on when to deploy Hadoop and when to take advantage of specialized Spark or machine-learning cloud-based services.
  • Advises that in most cases, there will be a place for both Hadoop and specialized cloud-based services.

Key questions answered

  • Why is Hadoop versus Spark a false dichotomy?
  • What are the scenarios where full Hadoop implementation and use of specialized Spark/machine-learning services in the cloud are warranted?

Table of contents

Ovum view

  • Summary
  • Hadoop and Spark: choose your bundle
  • It's about the breadth of workloads
  • And it's about data governance
  • The best of both worlds is best

Appendix

  • Further reading
  • Author

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