While digital twin technology was first pioneered in 2002, the digital twin market is rapidly expanding. The global digital twin market was capped at USD 3.1 billion in 2020, while some analysts predict the market will grow at a CAGR of 58 percent, projecting a market size of USD 48.2 billion by 2026.
The vast amount of use cases, and myriad benefits, have many organizations, specifically in the manufacturing industry, scrambling to either adopt and leverage the technology or first learn more about it.
Last week, ScaleOut Software announced extensions to their Digital Twin Streaming Service that integrate its Azure-based in-memory computing platform with Microsoft’s Azure Digital Twins cloud service.
With real-time, scalable message processing and no-code machine learning, this integration adds new capabilities for real-time analytics to Azure Digital Twins, with a variety of applications, such as predictive maintenance, logistics, telematics, disaster recovery, cyber and physical security, health-device tracking, IoT, smart cities, financial services, and e-commerce.
“We are excited to combine our in-memory computing technology with the popular Azure Digital Twins platform to deliver fast, scalable insights that help address real-time challenges across industries,” said Dr. William Bain, ScaleOut Software’s CEO, and founder. “By incorporating this technology, ScaleOut Software is enabling a new wave of applications for Azure Digital Twins, and we look forward to helping our customers take full advantage of this integration to meet their real-time monitoring and streaming analytics capabilities.”
The new ScaleOut Azure Digital Twins Integration is a set of extensions to the ScaleOut Digital Twin Streaming Service, which adds a real-time component to Azure digital twin models. With this integration, ScaleOut Software’s real-time components can perform low-latency message ingestion and processing with immediate access to their corresponding Azure digital twin’s properties instead of requiring Azure serverless functions to perform these functions. In addition, the ScaleOut Digital Twin Streaming Service provides real-time data aggregation, continuous query, and real-time visualization for Azure digital twin properties.
Key capabilities include:
- Fast, In-Memory Processing and State Storage: Integrating ScaleOut’s real-time components enables Azure digital twins to leverage in-memory computing and perform message processing with lower latency and faster access to state information than serverless functions. In-memory computing also boosts scalability to handle thousands or even millions of data sources.
- Integrated Connectivity to Azure IoT Hub: The ScaleOut Digital Twin Streaming Service connects directly with Azure IoT Hub (and other message hubs) using a scalable software architecture for message ingestion and replies.
- APIs for Accessing Azure Digital Twin Properties: ScaleOut’s real-time components incorporate APIs that can read and update state properties in Azure digital twin instances. They also make it possible for Azure digital twins to store complex data structures, such as event lists.
- New Real-Time Visualization Tools. The ScaleOut Azure Digital Twins Integration also enables continuous data aggregation and charting of state properties held in Azure Digital Twin instances. Users can now also perform continuous queries with geospatial visualization.
The integration widens the spectrum of use cases for Azure Digital Twins. Countless applications, from telematics to cyber security, must track thousands of data sources with low latency and react quickly to emerging issues. They can now use real-time components to accomplish this with their Azure Digital Twins models.
Real-time data aggregation and visualization provided by ScaleOut’s real-time components provide a continuous view of the dynamic state of Azure digital twin instances, optimizing situational awareness and enables managers to quickly identify and address emerging issues.
The solution combines state properties for real-time components with other properties tracked by Azure digital twins, giving users a unified view of all data when using the Azure Digital Twins Explorer GUI tool.
ScaleOut also said this new integration simplifies application development for message processing and accessing an Azure digital twin’s state. It also consolidates the code required by multiple serverless functions and avoids the need for application-specific code for message ingestion from Azure IoT Hub.
By integrating with Azure Digital Twins, ScaleOut’s real-time components automatically persist their state to Azure Digital Twins for offline storage, which the company claims enables them to save and restore their state across deployments on start-up while the real-time components run at fast, in-memory speed.
You can learn more here.