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Introduction

Today, when we come across new big data software companies, one of our first questions is to ask whether the underlying technology is open source. For big data, open source is increasingly becoming the norm.

Highlights

  • This report pinpoints the role of open source in big data platforms and analytics.

Features and Benefits

  • Helps enterprise customers assess when and where to expect open source solutions.
  • Helps big data-related vendors formulate their open source strategies.

Key questions answered

  • In what product domains of big data has open source become the norm for technology development and product delivery?
  • Why has open source grown in common with data platforms and machine-learning frameworks, but not with BI tools?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

The draw of open source

  • The rising barometer
  • Degrees of "open"
  • The scale factor

There are many open source models

  • Business model
  • Stewardship model
  • Licensing
  • Compared to proprietary software
  • The cloud, rather than open source, has driven the trend to subscriptions

Open source: market evidence

  • Enterprise applications
  • Databases
  • Analytic tools

Appendix

  • Methodology
  • Further reading
  • Author

Recommended Articles

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