When to Select Apache Spark, Hadoop or Hive for Your Big Data Project

It’s taken a few years to get some real traction, but Apache Spark is making remarkable gains at the expense of the original Hadoop ecosystem—due largely to its ability to process large volumes of data much faster than the older platform. Apache Spark is an open-source data processing engine built for speed, ease of use and sophisticated analytics. It is designed to process both batch processing and new workloads, such as analytics streaming, interactive queries and machine learning. IBM, to name only one major player, has invested heavily in Spark, which can give enterprises an advantage in multi-pass iterative machine learning algorithms, as well as interactive data interrogation on in-memory data sets. With a variety of Hadoop engine options from which to choose, it’s important for CTOs to consider which…


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