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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The digital twin model is worth a close look when designing the next generation of IoT applications.

IoT 45
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The Amazing Evolution of In-Memory Computing

ScaleOut Software

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. From Distributed Caches to Real-Time Digital Twins. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

Going back to the mid-1990s, online systems have seen relentless, explosive growth in usage, driven by ecommerce, mobile applications, and more recently, IoT. From Distributed Caches to Real-Time Digital Twins. For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing.

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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The digital twin model is worth a close look when designing the next generation of IoT applications.

IoT 40
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Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52
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A one size fits all database doesn't fit anyone

All Things Distributed

As I have talked about before, one of the reasons why we built Amazon DynamoDB was that Amazon was pushing the limits of what was a leading commercial database at the time and we were unable to sustain the availability, scalability, and performance needs that our growing Amazon.com business demanded. The opposite is true.

Database 167
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Expanding the Cloud: Introducing Amazon QuickSight

All Things Distributed

QuickSight is a fast, cloud native, scalable, business intelligence service for the 1/10th the cost of old-guard BI solutions. SPICE enables QuickSight to scale to many terabytes of analytical data and deliver response time for most visualization queries in milliseconds. Big data challenges.

Cloud 137