ScaleOut Software Introduces Breakthrough in Stream Processing with its v5.6 Release – 8/22/2017


Topic : What's New

ScaleOut Software Introduces Breakthrough in Stream Processing with its
v5.6 Release

Stateful stream processing tracks the dynamic state of data sources, offering a basis for deeper introspection and more effective alerting.

BELLEVUE, WA – August 22, 2017 ScaleOut Software, a leading provider of in-memory computing software, today announced 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 wide range of applications, including medical device monitoring, financial services, manufacturing and logistics, and the Internet of Things (IoT).

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 which do not provide explicit support for building digital twins, 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 make use of sophisticated models of data sources that can incorporate specialized, domain-specific algorithms and machine-learning techniques, while processing streaming data with high performance and automatic scalability and performing ongoing, data-parallel analytics to detect aggregate trends. The product includes comprehensive APIs for Java and C#, enabling fast development with widely-used languages and tools.

“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 for in-memory computing, ScaleOut StreamServer finally makes implementation of digital twin applications easily accessible to developers.”

In addition to providing an object-oriented platform for building stateful stream processing applications, ScaleOut StreamServer includes several features that simplify development:

  • Data-parallel analytics including MapReduce on live data and all features of ScaleOut ComputeServer
  • Kafka integration for receiving and sending event messages using the open source Apache Kafka messaging platform and incorporating automatic scaling of event processing to handle large workloads
  • ReactiveX APIs for fast event posting using the popular ReactiveX library with built-in dispatching of events to associated digital twin state information
  • Time Windowing APIs in Java and C# designed for easy integration of time window management of data streams into digital twin models

By integrating a fast, scalable stream-processing engine with an in-memory data grid, ScaleOut StreamServer provides a highly optimized platform for stateful stream processing. Unlike other stream processing platforms, such as Apache Flink, Spark, and Storm, ScaleOut StreamServer enables applications to implement object-oriented models of data sources. It then hosts large populations of data objects in memory and transparently distributes them across a cluster of commodity servers. Applications process incoming data streams in the context of these data objects, enabling the use of sophisticated algorithms for deep introspection. The platform delivers fast event execution by streamlining event delivery and minimizing the data motion required to access state information associated with digital twin models.

In addition to ScaleOut StreamServer, ScaleOut Software also is releasing other new features with version 5.6 of its in-memory data grid (IMDG) and in-memory computing platform, including:

  • NET Core Version 2.0 Distributed Cache and Session State Provider, enabling ASP.NET Core Version 2.0 applications to transparently access ScaleOut Software’s IMDG
  • Docker container support, allowing IMDG deployment within Docker containers distributed across a cluster of commodity servers
  • OpenSSL 1.1 support, which upgrades support for encryption of client/server communications using OpenSSL
  • Web-based Azure deployment, enabling deployment of a multi-server IMDG using web-based tools

Version 5.6 introduces features across ScaleOut Software’s portfolio of IMDG and in-memory computing products, which include ScaleOut StateServer®, ScaleOut StreamServer™, ScaleOut ComputeServer®, ScaleOut hServer® and ScaleOut GeoServer®. These products are available for use on premises and on the Azure and AWS public clouds.

About ScaleOut Software, Inc.

Founded in 2003, ScaleOut Software develops leading-edge software that delivers scalable, highly-available in-memory computing technology to a wide range of industries. ScaleOut Software’s in-memory computing platform enables operational intelligence by storing, updating, and analyzing fast-changing, live data so that businesses can capture perishable opportunities before the moment is lost. It has offices in Bellevue, Washington and Beaverton, Oregon. The company was founded by Dr. William L. Bain, whose previous company, Valence Research, developed and distributed web load-balancing software and was acquired by Microsoft Corporation.

For more information, please visit and follow us on Twitter at @scaleout_inc.

Media Contact:
Chris Villinger
ScaleOut Software

Leave a Reply

Your email address will not be published. Required fields are marked *

Try ScaleOut for free

Use the power of in-memory computing in minutes on Windows or Linux.

Try for Free

Not ready to download?