Compare IBM Spectrum Computing vs. MapR

Cancel
You must select at least 2 products to compare!
MapR Logo
Read 1 MapR review.
2,347 views|1,294 comparisons
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: July 2020.
431,670 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.

More IBM Spectrum Computing Pros »

The model creation was very interesting, especially with the libraries provided by the platform.

More MapR Pros »

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.

More IBM Spectrum Computing Cons »

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

More MapR Cons »

Pricing and Cost Advice
This solution is expensive.

More IBM Spectrum Computing Pricing and Cost Advice »

Information Not Available
report
Use our free recommendation engine to learn which Hadoop solutions are best for your needs.
431,670 professionals have used our research since 2012.
Ranking
8th
out of 26 in Hadoop
Views
331
Comparisons
179
Reviews
3
Average Words per Review
289
Avg. Rating
7.0
5th
out of 26 in Hadoop
Views
2,347
Comparisons
1,294
Reviews
1
Average Words per Review
657
Avg. Rating
8.0
Popular Comparisons
Compared 20% of the time.
Compared 19% of the time.
Compared 16% of the time.
Compared 10% of the time.
Also Known As
IBM Platform Computing
Learn
IBM
MapR
Video Not Available
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.
Offer
Learn more about IBM Spectrum Computing
Learn more about MapR
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
Top Industries
No Data Available
VISITORS READING REVIEWS
Computer Software Company47%
Wholesaler/Distributor8%
Comms Service Provider6%
Insurance Company6%
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: July 2020.
431,670 professionals have used our research since 2012.
IBM Spectrum Computing is ranked 8th in Hadoop with 3 reviews while MapR is ranked 5th in Hadoop with 1 review. IBM Spectrum Computing is rated 7.0, while MapR is rated 8.0. 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 MapR writes "Enables us to create preview models and has good scalability and stability ". IBM Spectrum Computing is most compared with Cloudera Distribution for Hadoop, whereas MapR is most compared with Cloudera Distribution for Hadoop, Amazon EMR, Apache Spark, BlueData and Hortonworks Data Platform.

See our list of best Hadoop vendors.

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.