Architecting for the Internet of Things

Making the most of the convergence of big data, fast data, and cloud

Publisher: O'Reilly
Released: June 2016

As the IoT continues to evolve, large vertical capabilities are converging to form an unexpected—and strong—new reference architecture for this emerging network. Machine-to-machine communications, big data, cloud computing, distributed systems, networking, mobile and telco, apps, and smart devices all contribute to IoT capabilities. This O’Reilly report examines the critical role that operational databases play in that convergence.

IoT data management platforms need to handle data in motion (fast data) as well as data at rest (big data). Legacy data systems aren’t designed to manage vast inflows of high-velocity data from multiple devices and sources. But as VoltDB CTO Ryan Betts explains, operational databases have the performance and scalability to combine data from analytics run against collected (big) data with the current state and readings of things (fast).

This report explains how operational databases enable IoT applications to fulfill four data management capabilities:

  • Fast Ingest: In-memory performance and horizontal scalability that provide a single ingestion point for high-velocity data feeds
  • Explore and Analyze: Real-time access to applications and querying engines
  • Act: The ability to trigger events and make decisions based on inbound streams
  • Export: The ability to export accumulated, filtered, enriched, or augmented data to downstream systems

About the author

Ryan Betts, VoltDB CTO, is one of the company’s founding developers. He’s been designing and building distributed systems and high-performance infrastructure software for almost 20 years. Chances are, if you’ve used the Internet, some of your ones and zeros passed through a slice of code he wrote or tested.

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