White Papers

Falling Out of the Clouds: When Your Big Data Needs a New Home

Running your Big Data Analytics in the Cloud? Is it becoming expensive? In this informative white paper for Data Center professionals, get exclusive insights into some of the tradeoffs of running Big Data workloads in the cloud and guidelines for when to bring it in-house. While AWS and other cloud providers can appear to offer flexibility, production Hadoop frameworks can suffer in the cloud due to lack of control, predictability and high costs.

This white paper will help you better understand when and why you may choose to move your Big Data out of the cloud, and offers insights on how to avoid the long deployment times and costs of managing your own clusters. You’ll discover how to  protect your hardware investment, improve predictability, and gain increased scalability by leveraging a unique approach that separates compute and storage resources.
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Big Data Architectural Principles

When the developers of the Hadoop/Big Data Architecture at Google were looking to design a platform that could store and process vast quantities of data at low cost, they developed several key principles for system architectures that Enterprises need to follow to achieve the goals of Big Data applications like Hadoop, Spark, Cassandra, and others. By following these principles, outlined in this paper, Enterprises can reap the same benefits first achieved by those large Web Scale organizations that developed them.
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Driving Scale-Out Data Center Infrastructure

Scale-out architecture was developed to deal with the growing avalanche of data and today thousands of Enterprises are piloting scale-out systems.   Despite the tremendous advantages of scale-out approaches, there are some significant problems which surface as the number and size of these deployments grow. This white paper offers a vision for a next generation scale-out infrastructure that addresses these challenges.
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Smarter Data Center Infrastructure for Scale-Out.

This white paper gives an overview of DriveScale’s overall product offering which consists of several tightly integrated software and hardware services aimed at providing flexibility, manageability and optimization to the scale-out data center. Included are DriveScale product performance results around throughput, IOPS and latency based on a set of Hadoop test workloads.
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