IBM Spectrum Computing vs. MapR

IBM Spectrum Computing is ranked 8th in Hadoop vs MapR which is ranked 6th in Hadoop with 2 reviews. The top reviewer of MapR writes "Because of their POSIX compliant file system, they can support read/write files over the WORM storage of their competitors". IBM Spectrum Computing is most compared with Red Hat CloudForms and Amazon EMR. MapR is most compared with Cloudera Distribution for Hadoop, Hortonworks Data Platform and Amazon EMR.
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IBM Spectrum Computing Logo
933 views|305 comparisons
MapR Logo
Read 2 MapR reviews.
3,770 views|1,496 comparisons
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Ranking
8th
out of 24 in Hadoop
Views
933
Comparisons
305
Reviews
0
Followers
223
Avg. Rating
N/A
6th
out of 24 in Hadoop
Views
3,770
Comparisons
1,496
Reviews
2
Followers
80
Avg. Rating
8.0
Top Comparisons
Compared 46% of the time.
Compared 25% of the time.
Compared 15% of the time.
Also Known As
IBM Platform Computing
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Overview

IBM Spectrum Computing uses intelligent workload and policy-driven resource management to optimize resources across the data center, on premises and in the cloud. Now up to 150X faster and scalable to over 160,000 cores, IBM provides you with the latest advances in software-defined infrastructure to help you unleash the power of your distributed mission-critical high performance computing (HPC), analytics and big data applications as well as a new generation open source frameworks such as Hadoop and Spark.

MapR MapReduce software makes Apache Hadoop more affordable and easier to use for big data analytics, business intelligence, distributed computing, and more.
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Learn more about IBM Spectrum Computing
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Sample Customers
London South Bank University, Transvalor, Infiniti Red Bull Racing, GenomicValence Health, Goodgame Studios, Pico, Terbium Labs, sovrn, Harte Hanks, Quantium, Razorsight, Novartis, Experian, Dentsu ix, Pontis Transitions, DataSong, Return Path, RAPP, HP
Find out what your peers are saying about Apache, Hortonworks, Cloudera and others in Hadoop.
310,362 professionals have used our research since 2012.
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