Compare HPE Ezmeral Data Fabric vs. IBM Spectrum Computing

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Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: January 2021.
456,719 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
"The model creation was very interesting, especially with the libraries provided by the platform."

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"This solution is working for both VTL and tape.""We are satisfied with the technical support, we have no issues.""The most valuable feature is the backup capability."

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Cons
"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."

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"This solution is no longer managing tapes correctly.""SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing.""We have not been able to use deduplication."

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Pricing and Cost Advice
Information Not Available
"This solution is expensive."

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456,719 professionals have used our research since 2012.
Ranking
6th
out of 22 in Hadoop
Views
2,011
Comparisons
1,107
Reviews
1
Average Words per Review
657
Rating
8.0
8th
out of 22 in Hadoop
Views
365
Comparisons
192
Reviews
3
Average Words per Review
283
Rating
7.3
Popular Comparisons
Compared 3% of the time.
Also Known As
MapR, MapR Data PlatformIBM Platform Computing
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Hewlett Packard Enterprise
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IBM
Overview

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.

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.

Offer
Learn more about HPE Ezmeral Data Fabric
Learn more about IBM Spectrum Computing
Sample Customers
Valence Health, Goodgame Studios, Pico, Terbium Labs, sovrn, Harte Hanks, Quantium, Razorsight, Novartis, Experian, Dentsu ix, Pontis Transitions, DataSong, Return Path, RAPP, HPLondon South Bank University, Transvalor, Infiniti Red Bull Racing, Genomic
Top Industries
VISITORS READING REVIEWS
Computer Software Company29%
Comms Service Provider18%
Financial Services Firm16%
Government6%
No Data Available
Company Size
REVIEWERS
Small Business43%
Large Enterprise57%
No Data Available
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: January 2021.
456,719 professionals have used our research since 2012.

HPE Ezmeral Data Fabric is ranked 6th in Hadoop with 1 review while IBM Spectrum Computing is ranked 8th in Hadoop with 3 reviews. HPE Ezmeral Data Fabric is rated 8.0, while IBM Spectrum Computing is rated 7.4. The top reviewer of HPE Ezmeral Data Fabric writes "Enables us to create preview models and has good scalability and stability ". On the other hand, the top reviewer of IBM Spectrum Computing writes "Provides stable backup for our databases and has good technical support ". HPE Ezmeral Data Fabric is most compared with Cloudera Distribution for Hadoop, Apache Spark, Hortonworks Data Platform, Amazon EMR and MongoDB, whereas IBM Spectrum Computing is most compared with Cloudera Distribution for Hadoop.

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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.