Version 2 of ScaleOut Software’s Digital Twin Service Yields Support for Application Development

ScaleOut Software, developer of scalable, highly available in-memory computing and streaming analytics technology software, announces version 2 of the ScaleOut Digital Twin Streaming Service for implementing streaming analytics in live systems via the digital twin model. The latest launch builds on the Version 1 iteration of the program, which consists of integrating machine learning into digital twins with Microsoft’s ML.NET library, intuitive business rules for creating digital twin models, and integrating Microsoft’s Azure Digital Twins.

“We are excited to release the second major release of our digital twin streaming service with exciting new features for developers,” said Dr. William Bain, CEO and Founder of ScaleOut Software. “Digital twins have the potential to significantly improve situational awareness for a variety of mission-critical applications. We believe this release will further accelerate the adoption of digital twins in applications tracking live systems with many data sources.”

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ScaleOut emphasizes the need to meet the modern needs of real-world applications and sees digital twins as the answer. With version 2, digital twins come with full support for tracking data sources for a range of live use cases that are business-critical, such as healthcare IT, disaster preparedness, and physical security systems.

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C#-based digital twins get more support with version 2, using .NET 6 for local deployment within Windows and Linux operating systems of C# digital twin models; previously, use of the .NET Framework was limited to Windows. Java or JavaScript for modeling digital twins is also available in the latest version and uses a built-in rules engine.

Version 2 of the ScaleOut Digital Twin Streaming Service includes built-in timers that, when created by developers, can initiate code execution for improved detection of missing or delayed messages from data sources. This ability, which notifies developers of signal alerts, is critical for live applications responsible for locating failed or unreliable devices – including smoke detectors and security system sensors.

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Unlike version 1’s limitation of automatically creating digital twins while messaging data sources, version 2 gives users more control by creating and triggering digital twins over file-based data. According to the vendor, this feature also supports the provision of an optional CSV file for the user interface when a model is provided for this purpose.

For more information about version 2, visit

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