MapReduce is a good example of choosing tools suitable to the task. I'll agree with the authors that there are certainly large DB systems that a traditional RDBMS is better suited or more optimal.
But the designers and avid users of MapReduce did not use it because it seemed a more optimal DB query engine. The utility|cost being optimized was not compute cycles or disk seeks or logappends, it was the developer time needed to construct another large-scale OLAP definition and an overall tolerance to hardware and system failure.
But the designers and avid users of MapReduce did not use it because it seemed a more optimal DB query engine. The utility|cost being optimized was not compute cycles or disk seeks or logappends, it was the developer time needed to construct another large-scale OLAP definition and an overall tolerance to hardware and system failure.