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Introduction

While most streaming data platforms focus primarily on the real-time uses of the data they handle, MapR’s approach is designed to integrate streaming analytics on the same cluster as historical analytics.

Highlights

  • While there are various streaming data publication/subscription services available, MapR Streams sits at a unique intersection of capabilities: it takes advantage of the converged MapR open core platform to seamlessly blend operational and analytical application capabilities in real time, for live insight and optimization.

Features and Benefits

  • Assesses the strengths of the MapR converged platform for use in streaming analytics via MapR Streams.
  • Analyzes the challenges that organizations face when combining insight from streaming data sources with other data sources, such as historical data.

Key questions answered

  • What differentiates MapR streams in the streaming data publication/subscription services market?
  • Why is the IoT and rise of connected devices causing a shift toward streaming data analytics platforms?
  • How can real-time streaming data insights be enriched with data from other sources without slowing down the analysis process?

Table of contents

Ovum view

  • Summary
  • MapR Streams speeds data forward, while keeping an eye on the rearview mirror
  • Converged platforms may offer the key to data context
  • Architectural considerations for adopters

Appendix

  • Further reading
  • Author

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