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IBM Spectrum Computing vs IBM Turbonomic comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

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

IBM Spectrum Computing
Ranking in Cloud Management
29th
Average Rating
7.8
Reviews Sentiment
5.9
Number of Reviews
9
Ranking in other categories
Hadoop (7th)
IBM Turbonomic
Ranking in Cloud Management
4th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
205
Ranking in other categories
Cloud Migration (3rd), Virtualization Management Tools (3rd), IT Financial Management (1st), IT Operations Analytics (11th), Cloud Analytics (1st), Cloud Cost Management (1st), AIOps (16th)
 

Mindshare comparison

As of May 2026, in the Cloud Management category, the mindshare of IBM Spectrum Computing is 1.5%, up from 1.1% compared to the previous year. The mindshare of IBM Turbonomic is 4.7%, down from 5.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Management Mindshare Distribution
ProductMindshare (%)
IBM Turbonomic4.7%
IBM Spectrum Computing1.5%
Other93.8%
Cloud Management
 

Featured Reviews

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.
reviewer1446966 - PeerSpot reviewer
Senior Systems Engineer at a university with 1,001-5,000 employees
The solution reduced our operational expenditures and is able to identify points before we even noticed them
The management interface seems to be designed for high-resolution screens. Somebody with a smaller-resolution screen might not like the web interface. I run a 4K monitor on it, so everything fits on the screen. With a lower resolution like 1080, you need to scroll a lot. Everything is in smaller windows. It doesn't seem to be designed for smaller screens. When I change the resolution to 1080, I only see half of what I would on my big 4K monitor. It would be annoying to have to scroll to see the flow chart. They have a flow chart that goes top to bottom like a tree. On a lower resolution, it might be nice if that scrolls horizontally because it's long, narrow, and tall. It's only three icons wide, but it's 15 icons tall. I think it would be helpful to have the ability to change that for a smaller screen and customize the widget.

Quotes from Members

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

Pros

"The most valuable aspect of the product is the policy driving resource management, to optimize the computing across data centers."
"Spectrum Computing is one of the best tools in the data management and services area, as it can process huge amounts of data with standardized data management and provides a great data governance capability."
"Easy to operate and use."
"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."
"The most valuable aspect of the product is the policy driving resource management, to optimize the computing across data centers."
"IBM's ability to cluster compute resources is impressive, with built-in support for scenarios like VR and active-active configurations,"
"The most valuable feature is the backup capability."
"I have utilized IBM Spectrum Computing's intelligent workload management feature through Insights, which is connected to the cloud."
"Turbonomic, per its design, finds bottlenecks and, depending on how it is configured, recommends actions and takes action to resolve the bottlenecks."
"I like the analytics that help us optimize compatibility. Whereas Azure Advisor tells us what we have to do, Turbonomic has automation which actually does those things. That means we don't have to be present to get them done and simplifies our IT engineers' jobs."
"Turbonomic is one of the best software solutions ever written."
"The system automatically sizes and moves resources based on the needs of the applications."
"We have saved more from cost avoidance on a recent expansion than the product will cost over three years."
"Customer service has always been exceptional and technical support has been very quick to respond and very knowledgeable."
"We are happy with Turbonomic."
"Customer service and support are one of the tops in the industry."
 

Cons

"SMB storage and HPC is not compatible and it should be supported by IBM Spectrum Computing."
"We have not been able to use deduplication."
"The deduplication software isn't quite up to speed with the market. While IBM has excellent compression technology, specifically on their FlashCore modules, they lag behind competitors such as NetApp in deduplication capabilities."
"Software sometimes is a little slower. It takes two or three days sometimes."
"This solution is no longer managing tapes correctly."
"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."
"We are not fully satisfied with this product at the moment because we are having issues with reliability."
"In Azure, it's not what you're using. You purchase the whole 8 TB disk and you pay for it. It doesn't matter how much you're using. So something that I've asked for from Turbonomic is recommendations based on disk utilization. In the example of the 8 TB disk where only 200 GBs are being used, based on the history, there should be a recommendation like, "You can safely use a 500 GB disk." That would create a lot of savings."
"The new HTML5 version is not as user friendly as I had hoped."
"There is an area where new workloads can be created and placed. I've had trouble with that feature and find it easier to create new machines directly in vCenter and let it get the address by Turbonomic after the fact."
"They could add a few more reports. They could also be a bit more granular. While they have reports, sometimes it is hard to figure out what you are looking for just by looking at the date."
"They have a long road map when we ask for certain things that will make the product better. It takes time, but that's understandable because there are other things that are higher on the priority list."
"The flash interface looks dated and is a little cluttered making navigating the portal less than optimal."
"It would be nice for them to have a way to do something with physical machines, but I know that is not their strength."
"The automation area could be improved, and the generic reports are poor. We want more details in the analysis report from the application layer. The reports from the infrastructure layer are satisfactory, but Turbonomic won't provide much information if we dig down further than the application layer."
 

Pricing and Cost Advice

"Spectrum Computing is one of the most expensive products on the market."
"This solution is expensive."
"We felt the pricing was very fair for the product. It is in no way prohibitive for larger deployments, unlike other similar product on the market."
"When we have expanded our licensing, it has always been easy to make an ROI-based decision. So, it's reasonably priced. We would like to have it cheaper, but we get more benefit from it than we pay for it. At the end of the day, that's all you can hope for."
"I have not seen Turbonomic's new pricing since IBM purchased it. When we were looking at it in my previous company before IBM's purchase, it was compatible with other tools."
"In the last year, Turbonomic has reduced our cloud costs by $94,000."
"I consider the pricing to be high."
"Everybody tells me the pricing is high. But the ROIs are great."
"The product is fairly priced right now. Given its capabilities, it is excellently priced. We think that the product will become self-funding because we will be able to maximize our resources, which will help us from a capacity perspective. That should save us money in the long run."
"I'm not involved in any of the billing, but my understanding is that is fairly expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
14%
Construction Company
10%
Outsourcing Company
9%
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
8%
Insurance Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise6
By reviewers
Company SizeCount
Small Business41
Midsize Enterprise57
Large Enterprise147
 

Questions from the Community

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...
What is your experience regarding pricing and costs for Turbonomic?
It offers different scenarios. It provides more capabilities than many other tools available. Typically, its price is set as a percentage of the consumption of some of our customers' services. The ...
What needs improvement with Turbonomic?
The implementation could be enhanced.
What is your primary use case for Turbonomic?
We use IBM Turbonomic to automate our cloud operations, including monitoring, consolidating dashboards, and reporting. This helps us get a consolidated view of all customer spending into a single d...
 

Also Known As

IBM Platform Computing
Turbonomic, VMTurbo Operations Manager
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

London South Bank University, Transvalor, Infiniti Red Bull Racing, Genomic
IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Find out what your peers are saying about IBM Spectrum Computing vs. IBM Turbonomic and other solutions. Updated: April 2026.
892,611 professionals have used our research since 2012.