Compare Apache Spark vs. IBM InfoSphere BigInsights

Apache Spark is ranked 1st in Hadoop with 7 reviews while IBM InfoSphere BigInsights is ranked 9th in Hadoop. Apache Spark is rated 8.0, while IBM InfoSphere BigInsights is rated 0. The top reviewer of Apache Spark writes "Fast performance and has an easy initial setup". On the other hand, Apache Spark is most compared with Spring Boot, AWS Lambda and Azure Stream Analytics, whereas IBM InfoSphere BigInsights is most compared with Hortonworks Data Platform, Cloudera Distribution for Hadoop and Apache Spark.
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Apache Spark Logo
11,048 views|9,201 comparisons
IBM InfoSphere BigInsights Logo
1,752 views|1,404 comparisons
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Ranking
1st
out of 24 in Hadoop
Views
11,048
Comparisons
9,201
Reviews
7
Average Words per Review
205
Avg. Rating
8.0
9th
out of 24 in Hadoop
Views
1,752
Comparisons
1,404
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 33% of the time.
Compared 11% of the time.
Also Known As
InfoSphere BigInsights
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Overview

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

IBM BigInsights delivers a rich set of advanced analytics capabilities that allows enterprises to analyze massive volumes of structured and unstructured data in its native format. The software combines open source Apache Hadoop with IBM innovations including sophisticated text analytics, IBM BigSheets for data exploration, IBM Big SQL for SQL access to data in Hadoop, and a range of performance, security and administrative features. The result is a cost-effective and user-friendly solution for complex, big data analytics.
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Sample Customers
NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi SolutionsCoherent Path Inc., Optibus, Delhaize America, Diyotta Inc., Ernst & Young, Teikoku Databank Ltd., NCSU, Vestas
Top Industries
REVIEWERS
Financial Services Firm29%
Software R&D Company29%
Marketing Services Firm14%
Healthcare Company14%
VISITORS READING REVIEWS
Software R&D Company30%
Comms Service Provider13%
Financial Services Firm9%
Media Company9%
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Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: December 2019.
382,547 professionals have used our research since 2012.
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