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"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
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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
Apache Spark is ranked 1st in Hadoop with 10 reviews while Google Cloud Dataflow is ranked 11th in Streaming Analytics. Apache Spark is rated 8.6, while Google Cloud Dataflow is rated 0.0. The top reviewer of Apache Spark writes "Good Streaming features enable to enter data and analysis within Spark Stream". On the other hand, Apache Spark is most compared with Spring Boot, Azure Stream Analytics, AWS Batch, AWS Lambda and Informatica Big Data Parser, whereas Google Cloud Dataflow is most compared with Apache NiFi, Apache Flink, Amazon Kinesis, Azure Stream Analytics and Talend Data Streams.
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