Move Your Computing to the Data
Cloud-based serverless functions offer an attractive approach to quickly deploying snippets of application code. However, their simplicity masks hidden challenges that they create for developers building complex workflows. Because serverless functions repeatedly retrieve and update stored data, they also can create additional overhead, performance issues, and costs.
Introducing ScaleOut Data Twins™. Now you can ship your functions to the data instead of the other way around. ScaleOut Data Twins hosts application data objects in memory for fast access. Using your predefined APIs for each data type, it processes incoming message requests to update data more than 10X faster. It also can transparently persist changes to cloud storage. Your workflows run fast and reliably, and they are easy to deploy and manage.
Experience the power of ScaleOut Data Twins by joining our beta program, which starts in June 2024. You can access the cloud service or run on-premises.
Use app-defined data types and APIs to avoid managing a large, unstructured collection of serverless functions.
Let highly available, in-memory computing eliminate configuration issues and quota limits.
Process messages where the data lives to avoid unnecessary data motion and enable fast, scalable performance.
Quickly build workflows that accept JSON-encoded messages from IoT hubs, message brokers, and cloud services.
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ScaleOut Data Twins lets you build complex cloud workflows without dealing with the complexity, reliability issues, performance limitations, and costs created by serverless functions. Its ground-breaking technology combines in-memory storage for application objects with fast execution of application-defined APIs.
Unlike actor models, ScaleOut Data Twins builds workflows using application data objects instead of code elements. Developers can implement APIs in C# or Java to ensure strongly typed access to user objects. Once uploaded to the service, these APIs are triggered by incoming message requests that process updates with zero data motion.
ScaleOut Data Twins integrates with cloud-hosted data stores, such as Amazon Dynamo DB, to transparently retrieve and update persisted objects. Objects migrate into memory when requested by incoming messages and stay resident while active. In-memory updates automatically flow to the cloud-hosted store.
JSON-encoded messages enable incoming requests from any cloud service. Highly available, in-memory storage and scalable processing seamlessly handle large workloads.
Because of its flexible software architecture, ScaleOut Data Twins lets you build workflows for a wide range of applications. For example, you can process messages from a large number of external data sources with application-defined objects that act as “digital twins.” You also can create networks of objects that process multi-step workflows by exchanging messages. Here are just a few examples:
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Process flight changes and update passenger itineraries.
Analyze telemetry from IoT devices to alert on emerging issues.
Manage updates to myriad components in a logistics network.
