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Real-Time Digital Twins Simplify Code in Streaming Applications

ScaleOut Software

Properties in the data objects for all data sources can be fed to real-time aggregate analysis (performed by the stream-processing platform) to immediately spot patterns of interest in the analytic results generated for each data source.

Code 52
article thumbnail

Real-Time Digital Twins Simplify Code in Streaming Applications

ScaleOut Software

Properties in the data objects for all data sources can be fed to real-time aggregate analysis (performed by the stream-processing platform) to immediately spot patterns of interest in the analytic results generated for each data source.

Code 52
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article thumbnail

Real-Time Digital Twins Simplify Code in Streaming Applications

ScaleOut Software

Properties in the data objects for all data sources can be fed to real-time aggregate analysis (performed by the stream-processing platform) to immediately spot patterns of interest in the analytic results generated for each data source.

Code 52
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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. For more than a decade, in-memory data grids (IMDGs) have proven their usefulness for storing fast-changing data in enterprise applications.

article thumbnail

Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. For more than a decade, in-memory data grids (IMDGs) have proven their usefulness for storing fast-changing data in enterprise applications.