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San Francisco, CA — June 2, 2009 — At the JavaOne Conference, ScaleOut Software today demonstrated innovative new extensions for its industry-leading distributed caching software product called ScaleOut StateServer®. With the release of version 4.1, ScaleOut Software further raises the bar for distributed caching by adding an object browser that lets users visually browse the contents of a distributed cache. This new capability gives developers and administrators a powerful new tool for managing a distributed cache. Version 4.1 also adds powerful and flexible support for integrating a distributed cache with a backing store, such as a database server or file system. These new features, combined with unique, Java-based "map/reduce" capabilities for grid computing, further extend ScaleOut Software's leadership for its enterprise-class, distributed caching products.
"Our customers continue to deepen their reliance on distributed caching to scale the performance of their mission-critical applications," said Dr. William L. Bain, founder and CEO of ScaleOut Software. "Our company's history has been that of identifying and delivering new caching technology to meet our customers' needs. We have added important new features for our Java customers which enable ScaleOut StateServer to further address these evolving needs with the most comprehensive, powerful, and best supported distributed caching platform possible."
Being able to view and manage objects stored in a distributed cache provides important insights into cache usage. The new ScaleOut StateServer Object Browser (Beta) gives developers and administrators a unique new tool for viewing the contents of the cache, showing the metadata for individual Java objects, and performing a number of management operations, such as querying the cache and clearing its contents. The object browser's capabilities dramatically increase the user's visibility into the contents of a distributed cache.
ScaleOut StateServer also now includes comprehensive support for automatically storing and retrieving cached objects from a backing store, such as a database server or file system. New Java APIs provide both synchronous "read through" and "write through" access to a backing store, as well as periodic, asynchronous "refresh ahead" and "write behind" access policies. To keep deployment as simple as possible, the user enables these features programmatically instead of building separate configuration files. A rich set of capabilities lets the user choose the appropriate policy for keeping the distributed cache in sync with a backing store to maximize application performance and minimize the load on the backing store.
Further deepening support for Java, ScaleOut StateServer's Grid Computing edition now includes unique Java APIs for performing data-parallel map/reduce computations on cached data. Called "parallel method invocation" (PMI), these APIs enable application developers to quickly and easily create data-parallel applications that automatically take advantage of the distributed cache's load-balancer to provide both multi-server and multi-core speedup. Recent tests on a key computational challenge in financial services have demonstrated PMI's value in shortening development cycles while delivering very high performance and efficient network usage.
About ScaleOut StateServer
ScaleOut StateServer provides distributed, in-memory caching for server farms and compute grids to boost application performance and offload database servers. Now in its fourth major release, ScaleOut StateServer has proven its ability to accelerate application performance every day on hundreds of production server farms across a wide range of industries including financial services, ecommerce, and many others. Its patented technology for scaling performance and replicating data enables it to deliver scalable access to cached data while maintaining high availability in case of server failures. Tests have shown that ScaleOut StateServer's performance quickly outpaces database servers as the load on a server farm grows. By using ScaleOut StateServer's distributed, in-memory cache for application data storage, developers can maintain fast response times while their server farm grows to handle increasing workloads.
While many Java-based distributed caching solutions are implemented solely for a single operating system, SOSS runs with native performance on Solaris, Linux, and Windows using a combination of Java and C within its implementation. These operating systems can be seamlessly intermixed within a single caching farm, and SOSS runs at native performance under all operating systems. Carefully-tuned multithreaded Java IO is used to produce robust, high-speed network access. With Hotspot enabled, network performance matches that of equivalent C++ and
ScaleOut StateServer provides powerful Java,
The ScaleOut GeoServer Option uses data replication to extend distributed caching across multiple, geographically distributed data centers so that they can share fast-changing workloads and be fully protected against site-wide failures. GeoServer's capabilities help IT managers meet the stringent performance and uptime needs of high-end Web sites and other mission-critical applications.
About ScaleOut Software, Inc.
ScaleOut Software develops software products that provide scalable, highly available caching for workload data in server farms and compute grids. 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 that was acquired by Microsoft Corporation and is now called Network Load Balancing within the Windows Server operating system.
For more information, contact David Brinker at firstname.lastname@example.org or visit [spam URL stripped]. ScaleOut Software, Inc. 10900 NE 4th Street, Suite 2300, Bellevue, WA 98004, T: 503-643-3422.
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Ice core drilling in the fast ice off Australia's Davis Station in East Antarctica by the Antarctic Climate and Ecosystems Co-Operative Research Centre shows that last year, the ice had a maximum thickness of 1.89m, its densest in 10 years. The average thickness of the ice at Davis since the 1950s is 1.67m.
A paper to be published soon by the British Antarctic Survey in the journal Geophysical Research Letters is expected to confirm that over the past 30 years, the area of sea ice around the continent has expanded."