Remove real-time-digital-twins-simplify-code-in-streaming-applications
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Real-Time Digital Twins Simplify Code in Streaming Applications

ScaleOut Software

Designing applications that extract real-time insights from streaming telemetry can be a daunting challenge. Event streams typically combine messages from many data sources, as shown below. The concept of “real-time digital twins” makes this possible.

Code 52
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Real-Time Digital Twins Simplify Code in Streaming Applications

ScaleOut Software

Designing applications that extract real-time insights from streaming telemetry can be a daunting challenge. Event streams typically combine messages from many data sources, as shown below. The concept of “real-time digital twins” makes this possible.

Code 52
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article thumbnail

Real-Time Digital Twins Simplify Code in Streaming Applications

ScaleOut Software

Designing applications that extract real-time insights from streaming telemetry can be a daunting challenge. Event streams typically combine messages from many data sources, as shown below. The concept of “real-time digital twins” makes this possible.

Code 52
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Real-Time Digital Twins Can Help Expedite Vaccine Distribution

ScaleOut Software

In-Memory Computing with Real Time Digital Twins: Fast and Agile. A software technology called in-memory computing has evolved over the last twenty years to grapple with the challenge of tracking and analyzing fast-changing data. Real-time digital twins are both easy to develop and easy to change as needs evolve.

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Why Use “Real-Time Digital Twins” for Streaming Analytics?

ScaleOut Software

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

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The Need for Real-Time Device Tracking

ScaleOut Software

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. The best they can usually do in real-time using general purpose tools is to filter and look for patterns of interest.

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Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

Whether it’s health-tracking watches, long-haul trucks, or security sensors, extracting value from these devices requires streaming analytics that can quickly make sense of the telemetry and intelligently react to handle an emerging issue or capture a new opportunity.

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