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The second release of the Databricks Spark platform-as-a-service (PaaS) highlights the growing popularity of R as programming language of choice among Spark developers. It simplifies deployment and visualizations developed in R.


  • This research analyzes how and why Databricks and the underlying Spark platform must -- and is -- evolving to a compute engine accessible from multiple programming languages and styles.

Features and Benefits

  • Analyzes why it is essential for the Spark compute engine to become accessible to multiple practitioner audiences.
  • Analyzes Databricks' strategy to make Spark accessible to R programmers.

Key questions answered

  • What enhancements is Databricks introducing in version 2 of its Spark PaaS platform?
  • Why is multilanguage access important for emerging big data compute engines like Spark?

Table of contents

Ovum view

  • Summary
  • To spur Spark adoption, widen the target audience
  • Don't forget about R
  • Other new features address diverse enterprise programming teams


  • Further reading
  • Author

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