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Apache Spark 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

Apache Spark
Ranking in Hadoop
1st
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
69
Ranking in other categories
Compute Service (6th), Java Frameworks (2nd)
IBM Spectrum Computing
Ranking in Hadoop
7th
Average Rating
7.8
Reviews Sentiment
5.9
Number of Reviews
9
Ranking in other categories
Cloud Management (32nd)
 

Mindshare comparison

As of August 2026, in the Hadoop category, the mindshare of Apache Spark is 14.2%, down from 19.2% compared to the previous year. The mindshare of IBM Spectrum Computing is 4.9%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Hadoop Mindshare Distribution
ProductMindshare (%)
Apache Spark14.2%
IBM Spectrum Computing4.9%
Other80.9%
Hadoop
 

Featured Reviews

Devindra Weerasooriya - PeerSpot reviewer
Data Architect at Devtech
Provides a consistent framework for building data integration and access solutions with reliable performance
The in-memory computation feature is certainly helpful for my processing tasks. It is helpful because while using structures that could be held in memory rather than stored during the period of computation, I go for the in-memory option, though there are limitations related to holding it in memory that need to be addressed, but I have a preference for in-memory computation. The solution is beneficial in that it provides a base-level long-held understanding of the framework that is not variant day by day, which is very helpful in my prototyping activity as an architect trying to assess Apache Spark, Great Expectations, and Vault-based solutions versus those proposed by clients like TIBCO or Informatica.
OmarIsmail1 - PeerSpot reviewer
Infrastructure Technical Specialist II at Clicks Group
Senior Technical Specialist appreciates intelligent workload management, strong support, and scalability
The best features of IBM Spectrum Computing are common across many of their storage products. The software is solid, meaning that the code is stable. They take business seriously, which is what IBM stands for - International Business Machines. They always maintain a business-oriented approach in their software development. It's not simply clicking through interfaces; in IBM software, they consider their actions, process flows, and workflows around business processes. It requires understanding IBM and their methodology, as the software operates accordingly. I have utilized IBM Spectrum Computing's intelligent workload management feature. We use Insights, which is connected to the cloud. This provides AI capabilities for analyzing the configuration, offering smart recommendations on new code, warning about bugs in current code, and suggesting configuration improvements through its advisor tool. The predictive analytics feature in IBM Spectrum Computing enables optimal software performance through Insights. However, being a storage administrator requires foundational knowledge and understanding beyond these tools. For troubleshooting, it's efficient in spotting bottlenecks, but understanding the terms and metrics is essential as it provides answers that need interpretation.

Quotes from Members

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

Pros

"As it uses in-memory data processing, Spark is very fast."
"The data processing framework is good."
"It allows the loading and investigation of very lard data sets, has MLlib for machine learning, Spark streaming, and both the new and old dataframe API."
"Spark is relatively easy to deploy, with rich features in handling big data."
"This solution provides a clear and convenient syntax for our analytical tasks."
"Having everything in the same framework has helped us out a lot."
"The deployment of the product is easy."
"The best features in Apache Spark that I appreciate are the fast database access, the data transformation, and the data exchange."
"Spectrum Computing's best features are its speed, robustness, and data processing and analysis."
"The best features of IBM Spectrum Computing are common across many of their storage products."
"I tell everyone that they should go with IBM Spectrum Computing."
"I have utilized IBM Spectrum Computing's intelligent workload management feature through Insights, which is connected to the cloud."
"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."
"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."
 

Cons

"Apache Spark's GUI and scalability could be improved."
"There were some problems related to the product's compatibility with a few Python libraries."
"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."
"Although you are able to perform complex transformations using Spark libraries, the support for SQL to perform transformations is still limited."
"It is useful for scientific purposes, but for commercial use of big data, it gives some trouble."
"When using Spark, users may need to write their own parallelization logic, which requires additional effort and expertise."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"Apache Spark should add some resource management improvements to the algorithms."
"Software sometimes is a little slower. It takes two or three days sometimes."
"We'd like to see some AI model training for machine learning."
"IBM's sales and support structure can be challenging."
"We have not been able to use deduplication."
"This solution is no longer managing tapes correctly."
"In Pakistan, IBM's disadvantage is the lack of OEM support and presence."
"The deduplication software isn't quite up to speed with the market."
"SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing."
 

Pricing and Cost Advice

"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."
"Spark is an open-source solution, so there are no licensing costs."
"It is quite expensive. In fact, it accounts for almost 50% of the cost of our entire project."
"I did not pay anything when using the tool on cloud services, but I had to pay on the compute side. The tool is not expensive compared with the benefits it offers. I rate the price as an eight out of ten."
"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
"Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."
"The product is expensive, considering the setup."
"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
19%
Construction Company
9%
Manufacturing Company
8%
Comms Service Provider
7%
Financial Services Firm
16%
Construction Company
13%
Manufacturing Company
13%
Comms Service Provider
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business28
Midsize Enterprise16
Large Enterprise33
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise6
 

Questions from the Community

What is your experience regarding pricing and costs for Apache Spark?
Apache Spark is open-source, so it doesn't incur any charges.
What needs improvement with Apache Spark?
I find that there really lacks the technical depth to do any recommendations for future updates of Apache Spark. I used it for two years for our prototype work and testing things, but because I had...
What is your primary use case for Apache Spark?
I attempted to use Apache Spark in one of our customer projects, but after the initial test, our customer moved to another technology and another database system. I do not have any final remarks on...
What is your experience regarding pricing and costs for IBM Spectrum Computing?
IBM Spectrum Computing consistently offers competitive pricing. When solutioning new implementations, IBM always presents the best solution and price. In a recent comparison with Pure Storage and N...
What needs improvement with IBM Spectrum Computing?
IBM Spectrum Computing had limitations with remote copy services between head office and disaster recovery sites. In the last year, IBM has improved the code by re-engineering it to policy-based re...
What is your primary use case for IBM Spectrum Computing?
The typical use case for IBM Spectrum Computing is that it's an all-rounder. It can be used in various scenarios, such as the retailer I work for that has batch processing. It's on-demand when perf...
 

Also Known As

No data available
IBM Platform Computing
 

Overview

 

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
London South Bank University, Transvalor, Infiniti Red Bull Racing, Genomic
Find out what your peers are saying about Apache Spark vs. IBM Spectrum Computing and other solutions. Updated: August 2026.
908,800 professionals have used our research since 2012.