This article is the third in an editorial series with a goal to provide direction for SaaS company thought leaders on ways to achieve higher levels of scalability and performance through use of in-memory computing technology.
While Linux clusters dominate HPC, there are many issues related to cost and complexity that can make open-source solutions challenging. In addition, determining real costs can be complex because every environment is different, and organizations will assess costs using their own methodologies and based on their own requirements and capabilities.
Download this whitepaper today to learn best practices for deploying GPFS-FPO as a file system platform for big data analytics. The goal of this paper is to guide the administrator through various decision points to ensure optimal configuration based on the Hadoop application components being deployed.
Data is exploring at large organization. So is the adoption of Hadoop. Hadoop’s potential cost effectiveness and facility for accepting unstructured data is making it central to modern, “Big Data” architectures. Yet, a significant obstacle to Hadoop adoption has been a shortage of skilled MapReduce coders.
This article is the fifth and last in an editorial series that will provide direction for enterprise thought leaders on ways of leveraging in-memory computing to analyze data faster, improve the quality of business decisions, and use the insight to increase customer satisfaction and sales performance.
This article is the fifth and last in an editorial series that has the goal to provide direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively in today’s climate of working to increase the value of corporate data assets.