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Cloudera Distribution for Hadoop vs IBM Spectrum Computing comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

Cloudera Distribution for H...
Ranking in Hadoop
2nd
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
50
Ranking in other categories
NoSQL Databases (8th)
IBM Spectrum Computing
Ranking in Hadoop
7th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
8
Ranking in other categories
Cloud Management (23rd)
 

Mindshare comparison

As of April 2025, in the Hadoop category, the mindshare of Cloudera Distribution for Hadoop is 25.0%, up from 23.0% compared to the previous year. The mindshare of IBM Spectrum Computing is 2.6%, up from 2.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop
 

Featured Reviews

Rok Dolinsek - PeerSpot reviewer
Enables on-premise implementation with powerful data processing capabilities
This is the only solution that is possible to install on-premise. Cloudera provides a hybrid solution that combines compute on cloud or on-premises. It includes all machine learning algorithms in the Spark machine learning library. All functionalities needed for a big data platform and ETL are on the platform, eliminating the need for other tools. It is scalable, ready for vertical scaling, and very powerful, offering numerous functionalities and configurations for generative AI.
Avra Jyoti Ghosh - PeerSpot reviewer
One of the best tools in the data management and services area
I mainly used Spectrum Computing for data management, governance, quality, and ETL activity Spectrum Computing's best features are its speed, robustness, and data processing and analysis.  Spectrum Computing is lagging behind other products, most likely because it hasn't been shifted to the…

Quotes from Members

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

Pros

"The main advantage is the storage is less expensive."
"The data science aspect of the solution is valuable."
"The features I find most valuable is that the solution is that it is easy to install and to work with. It starts with the installation and from there on the management is very simple and centralized."
"The solution's most valuable feature is the enterprise data platform."
"We're now able to store large volumes of data through Cloudera Distribution for Hadoop. We're able to push large volumes of data to the platform, and that used to be a challenge, especially when storing a terabyte of information. This is the area where Cloudera Distribution for Hadoop improved the organization."
"In terms of scalability, if you have enough hardware you can scale out. Scalability doesn't have any issues."
"With a cluster available, you can manage the security layer using the shared SDX - it provides flexibility."
"The tool's most interesting features are the distributed file system and unstructured data processing capability. Because we have a lot of unstructured data, like XML and social media logs, these features make it more valuable than the usual data warehousing solutions."
"IBM's ability to cluster compute resources is impressive, with built-in support for scenarios like VR and active-active configurations,"
"Spectrum Computing's best features are its speed, robustness, and data processing and analysis."
"The most valuable aspect of the product is the policy driving resource management, to optimize the computing across data centers."
"The most valuable feature is the backup capability."
"This solution is working for both VTL and tape."
"We are satisfied with the technical support, we have no issues."
"The comparison was challenging, but the IBM Spectrum Scale offered a balanced solution. Our engineers rated itsanalytics capabilities equally high as Pure Storage. For workload management, Spectrum Computing provided effective solutions that met our needs. Workload management is part of a complete solution that uses different tools. There were the cloud and HPC parts; within HPC, there were parts like liquid cooling, simple computing, storage, and orchestration. The orchestration team handled the workload management."
"Easy to operate and use."
 

Cons

"There are multiple bugs when we update."
"The user infrastructure and user interface needs to be improved, as well as the performance. The GUI needs to be better."
"There are better solutions out there that have more features than this one."
"The price of this solution could be lowered."
"I would like to see an improvement in how the solution helps me to handle the whole cluster."
"Currently, we are using many other tools such as Spark and Blade Job to improve the performance."
"The tool doesn't support reporting, and relational databases are still the major source of reporting data. Apache Iceberg will be launched soon within the Cloudera cluster for analytical purposes. The Cloudera Machine Learning aspect could be tuned and enhanced to enable us to host some predictive analytics machine learning and AI use cases."
"The tool's ability to be deployed on a cloud model is an area of concern where improvements are required."
"We'd like to see some AI model training for machine learning."
"SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing."
"Lack of sufficient documentation, particularly in Spanish."
"This solution is no longer managing tapes correctly."
"Spectrum Computing is lagging behind other products, most likely because it hasn't been shifted to the cloud."
"IBM's sales and support structure can be challenging."
"In Pakistan, IBM's disadvantage is the lack of OEM support and presence."
"We have not been able to use deduplication."
 

Pricing and Cost Advice

"When comparing with Oracle Sybase and SQL, it's cheaper. It's not expensive."
"I believe we pay for a three-year license."
"The pricing must be improved."
"The product’s price depends from project to project."
"The tool is not expensive."
"Cloudera Distribution for Hadoop is expensive, with support costs involved."
"I haven't bought a license for this solution. I'm only using the Apache license version."
"The price is very high. The solution is expensive."
"This solution is expensive."
"Spectrum Computing is one of the most expensive products on the market."
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Computer Software Company
15%
Educational Organization
12%
Manufacturing Company
7%
Financial Services Firm
40%
Computer Software Company
9%
Retailer
7%
Real Estate/Law Firm
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Cloudera Distribution for Hadoop?
The tool can be deployed using different container technologies, which makes it very scalable.
What is your experience regarding pricing and costs for Cloudera Distribution for Hadoop?
The price for Cloudera is average, yet it is very good compared to other solutions. It can be deployed on-premises, unlike competitors' cloud-only solutions.
What needs improvement with Cloudera Distribution for Hadoop?
It is quite complicated to configure and install. Integrating the platform into an information system is always a challenge, especially when starting with on-premise implementation. Integrating wit...
What needs improvement with IBM Spectrum Computing?
IBM's sales and support structure can be challenging. To work on an IBM deal, you often need to involve multiple specialists, each knowledgeable about only part of the product, rather than having a...
 

Also Known As

No data available
IBM Platform Computing
 

Overview

 

Sample Customers

37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC
London South Bank University, Transvalor, Infiniti Red Bull Racing, Genomic
Find out what your peers are saying about Cloudera Distribution for Hadoop vs. IBM Spectrum Computing and other solutions. Updated: March 2025.
845,040 professionals have used our research since 2012.