ScaleOut Expands Distributed Data Grids for Cloud

ScaleOut Software is shipping StateServer 5.0, a distributed data grid solution that allows devs to seamlessly access and migrate data across multiple locations-on-premise, virtual servers and even cloud.

Tags: Cloud, ScaleOut Software,

In specific, StateServer 5.0 expands automation for global data integration across multiple locations and creates a single logically coherent grid.  As a result, architects and devs receive seamless data integration in and out of the cloud, ability to conduct fully-parallel queries to .NET and Java-based objects, and support for Microsoft LINQ (Language Integrated Query).   

"Global data integration is avoids…replicating data [or] manually tracking, which are costly, error-prone and inefficient,” ScaleOut CEO William Bain told IDN. “By helping developers and architects access data transparently from any networked distributed data grid location, they can drastically simplify their applications and create important new capabilities,”  such as automating migration among sites, real-time sharing and even putting cloud computing options to better use, he added.

“We are making global data integration much more efficient for architects and developers letting them avoid re-stage,” IDN. “This includes task s such as moving data from one enterprise site to another, or even moving or integrating data among multiple locations-in-house, outsourced and even cloud.”

“Our main focus doing here is global data integration and pull it from remote site and maintain logical consistency,” Bain said. We conceived of this extension a year half ago, to help customers avoid the need to custom write these features outside their data grid by using messaging or WAN code, he added.

ScaleOut Server 5.0’s Top Improvements to Distributed Data Grid

Bain outlined key advantages to devs and architects from ScaleOut’s StateServer 5.0’s upgrades:

  • Simplicity StateServer 5.0 lets users automatically retrieve objects from the grid based on their properties, simplifying the structure of queries while maintaining fast access from all grid servers.  Java users enjoy the same parallel query functionality with standard APIs.  “Our architecture lets the enterprise or data architects maintain their application and data models as simple as possible, so they don’t have to think about remote access issues.”  
  • Access With StateServer 5.0, users can pull through data from another site, lock it, and when needed change it -- and have those changes visible to all connected remote sites.  “Customers used to send messages and do that," he added.   
  • Security StateServer 5.0 increases security, especially for companies with multiple applications accessing data within a single distributed data grid. Unauthorized or inadvertent access is prevented via a fully extensible authentication mechanism.  Other security extensions partition data into namespaces.
  • Governance and Management StateServer 5.0 also avoids any complicated multi-site governance issues, Bain added.  “There are no governance issues really.  We simply provide a logical infrastructure for developers, and they will simply set their own policies. 
  • Interop between J2EE and .NET Support for LINQ means .NET developers can access their companies’ data grids directly, without the need to query distributed data through a cache. StateServer 5.0 also supports fully parallel access to LINQ.  
  • Data Analysis StateServer 5.0 also allows multiple virtual servers to couple together and do a large data analysis in an elastic way.  “Parallel analysis doesn’t have to require a lot of network bandwidth,
  • Virtualization Support StateServer 5.0 also enables VMware users to license ScaleOut StateServer with an installer that will automatically create a VMWare distributed data grid appliance, providing a very fast and easy way to bring up the distributed data grid on VMWare virtual servers.

One timely example of StateServer 5.0’s benefits is for web-based shopping carts, Bain added.

For shopping carts, customers need to get data out of the cloud quickly for customers, payments, inventories, shipping and so on.  Shopping carts are also an example of how customers can better use distributed data grid technologies to keep data straight – without physically moving it or the need to validate remote data, xx told IDN. 

“You would host the StateServer data grid on the cloud and on-premise, so our load balancer can pull all data from the shopping carts and not require anything manual.  We’ve had customers pulling or distributing data to 20 locations and departments, and using ScaleOut they can get all their users the data they need without explicitly moving their data or building another discreet site. 

ScaleOut: Future Is Data Analysis in the Cloud
Looking to the future, Bain said StateServer 5.0 will become core foundation technology for a new generation of parallel data analysis using distributed grids.

“One big story for next year is that this approach lets us move toward parallel data analysis across the distributed data grid, and into the cloud,” Bain told IDN. “Today, our data grid is great for storing and moving data, but we can absolutely leverage multi-core architectures to do every efficient analysis.”