Reduce Hadoop Operational Cost by 50 Percent

Executive Summary

Archimedes, a healthcare modeling organization, develops the Archimedes Model, a clinically realistic, mathematical model of human physiology, diseases, interventions and healthcare systems. When the company sought to improve the time to results for its clients it developed new software called Aggregator using the open-source Big Data solution, Hadoop®, a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.

Archimedes then faced the challenge of deploying and managing Hadoop and needed to find a solution that made this easy and cost effective. They turned to Univa Grid Engine software to build a highly efficient cluster architecture to support running multiple applications. Archimedes estimates they have already cut costs on hardware and software up to 50% through adopting Univa Grid Engine software in the first step of the migration, without any compromise to overall performance.

From POC to Production: Faster

"If we didn't have Grid Engine software it would be a major investment to go live with Aggregator and Hadoop."
Katrina Montinola, Archimedes

As Big Data technologies enter the enterprise, they must coordinate and integrate with existing systems management best practices in the data center. While benefits from Big Data applications are immense they can be quickly undermined by poor utilization in a silo or the inability to share.

  • Shared infrastructure reduces the costs of deploying Hadoop by up to 50%
  • Policy driven scheduling increases utilization and control
  • Support for dynamic and multiple instances of Hadoop and other applications on a shared cluster
  • Sharing supports high utilization and resource availability

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