Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory
The Hortonworks Data Platform is acclaimed for its robust handling of big data, offering scalable solutions for data storage optimization and advanced analytics. Users benefit from its seamless processing of both streaming and batch data, and efficient maintenance of data lakes for improved governance. Key features include comprehensive security and seamless integration with existing analytics tools, significantly enhancing organizational efficiency and decision-making capabilities.
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