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Links 1 through 10 of 50 by Ken Robson tagged data

Site concerning the challenges facing the scale-out of Web 2.0 architectures.

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At Xeround, we have developed a live and scalable Intelligent Data Grid™ based on a groundbreaking cloud computing database paradigm. With over three years of research and development and our first customer deployments underway, Xeround is providing the industry's first distributed data grid complete with true data virtualization capabilities.

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Taxonomy diagram for cloud computing including vendors.

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At Xeround, we have developed a live and scalable Intelligent Data Grid™ based on a groundbreaking cloud computing database paradigm. With over three years of research and development and our first customer deployments underway, Xeround is providing the industry's first distributed data grid complete with true data virtualization capabilities.

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We are currently in the biggest data center construction boom in history. At the same time, this boom is dramatically weakening the future flexibility and financial performance of information technology.

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This is a book about ehcache, a widely used open source Java cache. Ehcache has grown in size and scope since it was introduced in October 2003. As people used it they often noticed it was missing a feature they wanted. Over time, the features that were repeatedly asked for, and make sense for a Cache, have been added.

Ehcache is now used for Hibernate caching, data access object caching, security credential caching, web caching, application persistence and distributed caching. The biggest issue faced by Ehcache users at the time of writing is understanding when and how to use these features.

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Stork is a batch scheduler specialized in data placement and data movement, which is based on the concept and ideal of making data placement a first class entity in a distributed computing environment. Stork understands the semantics and characteristics o

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The Mariposa distributed database management system is an ongoing research project at the University of California at Berkeley.
Mariposa addresses fundamental problems in the standard approach to distributed data management. We believe that the underlying

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Anyone who has delved into data from the real world knows it can be messy. Survey takers can write down the wrong response. People entering data into a computer can type in the wrong numbers. Computers sometimes garble data because of software bugs (espe

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The goal is to provide I/O consolidation over Ethernet reducing network complexity in the Datacenter.

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