Why is Spark So Hot? The amount of data generated around the globe each day is 2.5 exabytes (Adepta, March 2015), and the big data market reached $27.4 billion in 2014 (Wikibon, March 2015). Spark is ...

Apache Spark is one of the quickest tools, which is apt for large data-scale processing. At times, it even considered as one the topmost data processing solution, which is even quicker than platforms ...

Apache Spark is a project designed to accelerate Hadoop and other big data applications through the use of an in-memory, clustered data engine. The Apache Foundation describes the Spark project this ...

For several years big data has been nearly synonymous with Hadoop, a relatively inexpensive way to store huge amounts of data on commodity servers. But recently banks have started using an alternative ...

The misuse of data analytics is well documented — data being shoehorned to back up entrenched views, used selectively in petty corporate infighting, or simply misinterpreted. But even when done ...

What’s the difference between SPARK 2014 and Apache Spark? Actually, the answer is quite easy. SPARK 2014 is a programming environment based on the Ada programming language. Apache’s open-source SPARK ...

There is more to big data than Hadoop, but the trend is hard to imagine without it. Its distributed file system (HDFS) is helping businesses to store unstructured data in vast volumes at speed, on ...

Traditional relational databases have been highly effective at handling large sets of structured data. That’s because structured data conforms nicely to a fixed schema model of neat columns and rows ...

As we’ve touched on before, Hadoop was designed as a batch-oriented system, and its real-time capabilities are still emerging. Those eagerly awaiting this next evolution will be pleased to hear about ...

The quest to replace Hadoop’s aging MapReduce is a bit like waiting for buses in Britain. You watch a really long time, then a bunch come along at once. We already have Tez and Spark in the mix, but ...