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Lower Big Data Hardware TCO with Hadoop
December 11, 2015 Blog big data Hadoop

This article was originally published by and can be viewed in full here

Apache Hadoop unquestionably delivers ROI by increasing the flexibility of data management/storage, processing, and analytics abilities. And it’s logical to assume that “commodity” servers translate into cost savings. But the truth is that while Hadoop can and does deliver significant cost reductions and revenue gains, much depends on the actual deployment.

The true total cost of ownership (TCO) of any distributed system is dependent on architecture and best practice IT operations. The cost of purchasing and maintaining hardware aside, performance, reliability and scalability are critical to real TCO—a sluggish, unstable system may cost less for its physical structure, but will drain capital as well as operational expense resources from the company.

Hadoop itself is not a magical solution that makes data management faster, easier, and cheaper. The architectural differences between Hadoop distributions can save companies 20-50% in TCO.