ScaleOut Software Adds Support for Distributed Caching in ASP.NET Core 2.0
with its v5.6 Release

Industry-leading in-memory data grid also adds stateful stream processing and other features for in-memory computing in version 5.6.

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 adds support for distributed caching to Microsoft’s ASP.NET Core 2.0 platform that lets application developers transparently take advantage of the company’s industry-leading, in-memory data grid software technology. Version 5.6 also extends its in-memory computing software to offer breakthrough new capabilities for stream processing on both Windows and Linux.

Called ScaleOut StateServer®, ScaleOut Software’s in-memory data grid software product now implements ASP.NET’s IDistributedCache interface to transparently enable both distributed caching and session state storage for ASP.NET Core 2.0 applications. Microsoft’s newly introduced version of the ASP.NET platform now can make use of ScaleOut StateServer’s in-memory data grid technology. Battle-tested for more than a decade in more than 400 mission-critical commercial deployments, ScaleOut’s in-memory data grid includes several advanced features, such as transparent scaling, integrated high availability, distributed LINQ query, data-parallel analytics, and WAN-based replication.

“We are very pleased to add support for ASP.NET Core 2.0 so quickly after the platform’s release,” said Dr. William Bain, founder and CEO of ScaleOut Software. “This continues our drive to meet the needs of .NET developers as we add new capabilities to our in-memory data grid products and provide technical leadership for in-memory computing in .NET.”

Version 5.6 also introduces ScaleOut StreamServer™, a new feature set for “stateful” stream processing using ScaleOut Software’s in-memory computing technology. 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. The in-memory computing platform delivers fast event execution by streamlining event delivery and minimizing the data motion required to access state information associated with digital twin models. ScaleOut StreamServer includes comprehensive APIs for C# and Java, enabling fast development with widely-used languages and tools.

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 and all features of ScaleOut StateServer Pro
• 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

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:

• Web-based Azure deployment, enabling deployment of a multi-server IMDG to Microsoft’s Azure cloud platform using web-based tools
• 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

Version 5.6 introduces features across ScaleOut Software’s portfolio of IMDG and in-memory computing products, which include ScaleOut StateServer®, ScaleOut StreamServer™, ScaleOut StateServer Pro®, 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 www.scaleoutsoftware.com and follow us on Twitter at  @scaleout_inc.

Media Contact:
Chris Villinger
ScaleOut Software
1-503-643-3422
marketing@scaleoutsoftware.com