Compare IBM Spectrum Computing vs. Spark SQL

IBM Spectrum Computing is ranked 14th in Hadoop while Spark SQL which is ranked 8th in Hadoop with 1 review. IBM Spectrum Computing is rated 0, while Spark SQL is rated 8.0. On the other hand, the top reviewer of Spark SQL writes "A good stable and scalable solution for processing big data". IBM Spectrum Computing is most compared with Cloudera Distribution for Hadoop, whereas Spark SQL is most compared with Apache Spark, AtScale and Informatica Big Data Parser.
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IBM Spectrum Computing Logo
984 views|249 comparisons
Spark SQL Logo
825 views|511 comparisons
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: July 2019.
359,759 professionals have used our research since 2012.
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359,759 professionals have used our research since 2012.
Ranking
14th
out of 24 in Hadoop
Views
984
Comparisons
249
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
8th
out of 24 in Hadoop
Views
825
Comparisons
511
Reviews
1
Average Words per Review
226
Avg. Rating
8.0
Top Comparisons
Compared 24% of the time.
Compared 18% 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.

Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed. There are several ways to interact with Spark SQL including SQL and the Dataset API. When computing a result the same execution engine is used, independent of which API/language you are using to express the computation. This unification means that developers can easily switch back and forth between different APIs based on which provides the most natural way to express a given transformation.
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Sample Customers
London South Bank University, Transvalor, Infiniti Red Bull Racing, Genomic
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Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: July 2019.
359,759 professionals have used our research since 2012.
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.
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