Compare IBM Spectrum Computing vs. Netezza Analytics

IBM Spectrum Computing is ranked 6th in Hadoop with 3 reviews while Netezza Analytics is ranked 5th in Hadoop with 5 reviews. IBM Spectrum Computing is rated 7.0, while Netezza Analytics is rated 7.4. The top reviewer of IBM Spectrum Computing writes "Provides stable backup for our databases and has good technical support ". On the other hand, the top reviewer of Netezza Analytics writes "A high-performance solution to create reports from our data mart, but the scalability needs improvement". IBM Spectrum Computing is most compared with Cloudera Distribution for Hadoop, whereas Netezza Analytics is most compared with Apache Spark, Cloudera Distribution for Hadoop and Spark SQL. See our IBM Spectrum Computing vs. Netezza Analytics report.
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Find out what your peers are saying about IBM Spectrum Computing vs. Netezza Analytics and other solutions. Updated: November 2019.
383,444 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
We are satisfied with the technical support, we have no issues.The scalability of the solution is good.This solution is working for both VTL and tape.

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The need for administration involvement is quite limited on the solution.The most valuable feature is the performance.For me, as an end-user, everything that I do on the solution is simple, clear, and understandable.The performance of the solution is its most valuable feature. The solution is easy to administer as well. It's very user-friendly. On the technical side, the architecture is simple to understand and you don't need too many administrators to handle the solution.

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Cons
SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing.The initial setup is not so complex. However, the day-to-day administration is complex and there are far too many manual intervention requirements.This solution is no longer managing tapes correctly.

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I'm not sure of IBM's roadmap currently, as the solution is coming up on its end of life.The Analytics feature should be simplified.The solution could implement more reporting tools and networking utilities.The hardware has a risk of failure. They need to improve this.This product is being discontinued from IBM, and I would like to have some kind of upgrade available.The most valuable features of this solution are robustness and support.

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Pricing and Cost Advice
This solution is expensive.

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The annual licensing fees are twenty-two percent of the product cost.

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report
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Ranking
6th
out of 24 in Hadoop
Views
303
Comparisons
158
Reviews
3
Average Words per Review
289
Avg. Rating
7.0
5th
out of 24 in Hadoop
Views
738
Comparisons
468
Reviews
4
Average Words per Review
422
Avg. Rating
7.5
Top Comparisons
Compared 42% of the time.
Compared 10% 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.

IBM Netezza Analytics is an embedded, purpose-built, advanced analytics platform that empowers analytic enterprises to meet and exceed their business demands. As features, it can predict with more accuracy, deliver predictions faster and respond rapidly to changes.
Offer
Learn more about IBM Spectrum Computing
Learn more about Netezza Analytics
Sample Customers
London South Bank University, Transvalor, Infiniti Red Bull Racing, GenomicA leading online advertising network
Find out what your peers are saying about IBM Spectrum Computing vs. Netezza Analytics and other solutions. Updated: November 2019.
383,444 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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