Anonymous UserTechnical Consultant at a tech services company
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
Earn 20 points
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
Forward-leaning companies win market share because they leverage data more effectively than their competitors. Unlock the potential of your data assets with HPE Ezmeral Data Fabric (formerly MapR Data Platform). Empower your data science, analytics, and business teams by simplifying data management on a globally distributed scale. All with enterprise-grade reliability, security, and performance.
Apache Spark is ranked 1st in Hadoop with 11 reviews while HPE Ezmeral Data Fabric is ranked 9th in Hadoop. Apache Spark is rated 8.6, while HPE Ezmeral Data Fabric 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 Vert.x, whereas HPE Ezmeral Data Fabric is most compared with Cloudera Distribution for Hadoop, Hortonworks Data Platform, BlueData, Amazon EMR and IBM Spectrum Computing.
See our list of best Hadoop vendors.
We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.