MapReduce wasn't designed for iterative algorithms or streaming data, whereas Google Dataflow and Spark (http://spark.apache.org/ http://spark.apache.org/) make

MapReduce wasn't designed for iterative algorithms or streaming data, whereas Google Dataflow and Spark (http://spark.apache.org/ http://spark.apache.org/) make iterative algoritms easy. It's a much simpler programming paradigm, and it allows you to do iterative graph-processing and machine-learning algos (http://spark.apache.org/mllib/ http://spark.apache.org/mllib/) that are impractical on MapReduce. For example, Spark provides the primitives needed to build GraphX (http://amplab.github.io/graphx/ http://amplab.github.io/graphx/, http://spark.apache.org/graphx/ http://spark.apache.org/graphx/), which is essentially GraphLab on Spark.