Architecting Networks for the Big Data Lake

This conflict between data locality and scale/efficiency is likely to remain one of the key challenges for Hadoop going forward, says Hedvig CEO Avinash Lakshman. As he explained to InfoStor recently, tools like MapReduce can effectively manage DAS architectures throughout the lake, but it results in islands of Big Data storage that work against the goal of quickly and easily comparing vast data sets against each other to gain insight.

 

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This conflict between data locality and scale/efficiency is likely to remain one of the key challenges for Hadoop going forward, says Hedvig CEO Avinash Lakshman. As he explained to InfoStor recently, tools like MapReduce can effectively manage DAS architectures throughout the lake, but it results in islands of Big Data storage that work against the goal of quickly and easily comparing vast data sets against each other to gain insight.
2016-11-1