New ScaleOut v5.6 release now offers analysis of streaming data; tracking behavior of data sources

In-memory computing software company ScaleOut Software announced Tuesday the version 5.6 release of its in-memory data grid and computing platform. This release introduces ScaleOut StreamServer, a new software platform for “stateful” stream processing.

This platform offers important new capabilities for analyzing streaming data by enabling applications to model and track the behavior of data sources instead of just analyzing the telemetry they emit. This allows applications to implement deeper introspection and more effective alerting on streaming data across a range of applications, including medical device monitoring, financial services, manufacturing and logistics, and the Internet of Things (IoT).

ScaleOut StreamServer’s architecture delivers capabilities and peak performance for stateful stream processing. It processes incoming data streams within an in-memory data grid — where the data lives — ensuring minimum latency and peak throughput. Other platforms need to pull state information from remote data stores, such as database servers and distributed caches; this creates delays and network bottlenecks.

Instead, ScaleOut StreamServer delivers streamed events directly to their associated state data, enabling immediate, fully contextual processing. Its transparently scalable platform minimizes the latency required for event tracking and analysis, ensuring timely feedback and/or alerts for the largest workloads.

By integrating a fast, scalable stream-processing engine with an in-memory data grid, ScaleOut Software has created a uni ed software platform for the next-generation of stream processing.

Unlike mainstream platforms such as Apache Flink, Spark and Storm, ScaleOut StreamServer enables applications to implement object-oriented models of data sources. It can host large populations of data objects in memory on a cluster of commodity servers and dispatch incoming streaming events to these objects for analysis. Applications now can process incoming data streams in a rich context of evolving state, enabling the use of sophisticated algorithms while delivering blazingly fast event handling.

Stateful stream processing describes a new approach to application development that models streaming data sources in software as “digital twins” of their real-world siblings. Unlike traditional stream processing platforms, ScaleOut StreamServer offers an easy-to-use, object-oriented model that has been tightly integrated with a scalable, highly available in-memory compute engine. This enables applications to incorporate specialized, domain-specific algorithms and machine-learning techniques, while processing streaming data with high performance and automatic scalability. The product includes comprehensive APIs for Java and C#.

“We are excited to introduce a new platform for the next generation of stream processing,” said Dr. William Bain, founder and CEO of ScaleOut Software. “Because of its ability to offer much deeper introspection on streaming data, the digital twin model has captured the imagination of the stream processing community. With its object-oriented architecture, ScaleOut StreamServer finally makes implementation of digital twin applications easily accessible to developers.”

ScaleOut StreamServer includes integrated data-parallel analytics, support for Kafka messaging, ReactiveX APIs, and Time Windowing libraries. Version 5.6 of ScaleOut’s in-memory computing platform also adds support for ASP.NET Core 2.0 distributed caching and Docker containers.


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