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DataRobot vs IBM Turbonomic 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:
 

ROI

Sentiment score
9.0
DataRobot enhanced prediction accuracy, reduced analysis time, simplified processes, and improved efficiency, leading to better decisions and cost savings.
Sentiment score
7.2
IBM Turbonomic offers quick ROI by reducing hardware costs, optimizing resources, and decreasing operational expenses through automation and efficiency.
On average, we're saving about 10 to 15 hours per project.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Customer Service

Sentiment score
7.5
DataRobot excels in customer service and scalability, but could improve response speed and documentation for large datasets.
Sentiment score
8.9
IBM Turbonomic's customer service is highly rated for its responsiveness, knowledge, and effectiveness, despite some mixed post-acquisition experiences.
They answer all my questions and share guidance on using DataRobot scripts if certain functionalities are not available in the UI.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
Being cloud-hosted enables automatic resource scaling, which supports collaboration across teams.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Scalability Issues

Sentiment score
4.6
DataRobot is scalable, integrates easily, automates processes, supports multiple models, and handles large data volumes efficiently.
Sentiment score
6.9
IBM Turbonomic is scalable, seamlessly integrating with various environments while its licensing supports expansion, focusing on additional requirements.
 

Stability Issues

Sentiment score
7.7
DataRobot is praised for stability and reliability, with enhancements improving user satisfaction across diverse analytics scenarios.
Sentiment score
7.4
IBM Turbonomic is praised for stability and robust performance, with minor update issues swiftly resolved by support.
 

Room For Improvement

DataRobot faces customization, integration, and performance challenges; improved AI support, transparency, and community engagement are needed.
IBM Turbonomic needs an improved interface, better reporting, clearer documentation, more integrations, and a stable, mobile-compatible platform.
There is a lack of transparency in the models; sometimes it feels like a black box.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
 

Setup Cost

<p>DataRobot provides scalable, cost-effective AI solutions with flexible pricing tailored to enterprise needs and usage volume.</p>
IBM Turbonomic offers flexible, competitive pricing models, providing value through resource optimization and reducing hardware expenses effectively.
The setup cost was minimal because it's cloud-hosted, eliminating the need for heavy on-premises infrastructure, allowing us to start using it immediately after purchase.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Valuable Features

DataRobot automates feature engineering and model testing, enhancing productivity and decision-making with user-friendly, scalable integration.
IBM Turbonomic enhances efficiency through automation, capacity management, reporting, and planning, optimizing resource allocation and infrastructure decisions.
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
DataRobot has positively impacted our organization in many ways. First, it has improved efficiency; tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
 

Categories and Ranking

DataRobot
Ranking in AIOps
15th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
6
Ranking in other categories
Predictive Analytics (5th), AI Development Platforms (15th), AI Observability (66th), AI Finance & Accounting (4th)
IBM Turbonomic
Ranking in AIOps
11th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
205
Ranking in other categories
Cloud Migration (6th), Cloud Management (5th), Virtualization Management Tools (4th), IT Financial Management (1st), IT Operations Analytics (5th), Cloud Analytics (1st), Cloud Cost Management (1st)
 

Mindshare comparison

As of January 2026, in the AIOps category, the mindshare of DataRobot is 1.0%, up from 0.5% compared to the previous year. The mindshare of IBM Turbonomic is 1.0%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AIOps Market Share Distribution
ProductMarket Share (%)
IBM Turbonomic1.0%
DataRobot1.0%
Other98.0%
AIOps
 

Featured Reviews

Naqash Ahmed - PeerSpot reviewer
Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
Automation has improved efficiency and decision-making while big data handling and transparency still need work
Aside from the many advantages of DataRobot, I believe there are areas that could be improved based on my experience. There is a lack of transparency in the models; sometimes it feels like a black box. For example, when I uploaded a large data set of about two gigabytes for processing, the time taken was slower than expected. Additionally, the handling of bigger data sets could be better, as it performs extremely well with smaller datasets but can lag with larger ones. The integration with some other tools used in our organization can also be challenging, and more flexibility for custom pre-processing and advanced model tuning would be beneficial. In terms of support and documentation, I believe improvements are needed. For instance, the response time from DataRobot could be quicker, which would be appreciated when we need assistance. The documentation is generally sufficient, but it can be lengthy and could use more real-world examples and step-by-step tutorials for better clarity. Lastly, creating a client community where users can share experiences and solutions might enhance the overall value and learning curve.
Dan Ambrose - PeerSpot reviewer
Infrastructure Engineer 4 at a tech vendor with 1,001-5,000 employees
Helps visibility, bridges the data gap, and frees up time
We use IBM Turbonomic in a hybrid cloud environment. Although it supports multi-cloud capabilities, we currently operate in a single-cloud setting. Turbonomic offers visibility into our environment's performance, spanning across applications, underlying infrastructure, and protection resources. The visibility and analytics help to bridge the data gap between disparate IT teams such as applications and infrastructure. This is important for awareness collaboration, cost saving, and helping to design and improve our application. Enhanced visibility and data analytics have contributed to a significant reduction in our mean time to resolve. Tools like Turbonomic provide crucial visualization and insights, empowering us to make data-driven decisions instead of relying on assumptions as we did before. This newfound transparency translates to a massive improvement, going from complete darkness to having a clear 100 percent view of the situation. Although our applications are not optimized for the cloud we have seen some improvement in response time. IBM Turbonomic empowers us to achieve more with fewer people thanks to automation. Previously, customers frequently contacted us requesting resource increases to resolve issues. Now, we have a tool that allows us to objectively assess their needs, leading to a deeper understanding of our applications. This solution also generates significant cost savings in the cloud and optimizes hardware utilization within our data centers. Its AI algorithm intelligently allocates servers on hosts, maximizing efficiency without compromising performance. By fine-tuning resource allocation without causing performance bottlenecks, Turbonomic extends the lifespan of existing hardware, postponing the need for new purchases. This effectively stretches our capital expenditure budget. We started to see the benefits of IBM Turbonomic within the first 60 days. IBM is a fantastic partner. Their tech support has been outstanding, and the product itself is excellent - a very solid offering. By automating resource management with Turbonomic, our engineers are freed up to focus on more strategic initiatives like innovation and ongoing organizational projects. Previously, manually adding resources was a time-consuming process that interrupted workflows. Now, automation handles scaling efficiently, saving us thousands of man-hours and significant costs. It has illuminated the need for SetOps. It has highlighted areas of overspending, and the actions we've taken have demonstrated significant cost savings. IBM Turbonomic has positively impacted our overall application performance. IBM Turbonomic has helped reduce both CAPEX and OPEX. It has also significantly reduced cloud build times.
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
12%
Computer Software Company
10%
Retailer
8%
Financial Services Firm
11%
Computer Software Company
11%
Manufacturing Company
9%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business41
Midsize Enterprise57
Large Enterprise147
 

Questions from the Community

What is your experience regarding pricing and costs for DataRobot?
While pricing falls more under my IT colleagues, from my perspective, the overall experience feels justified. The premium pricing is reasonable for the value provided, and I'd say it's worth the in...
What needs improvement with DataRobot?
Aside from the many advantages of DataRobot, I believe there are areas that could be improved based on my experience. There is a lack of transparency in the models; sometimes it feels like a black ...
What is your primary use case for DataRobot?
My main use case for DataRobot is to perform predictive analysis and automation of machine learning workflows. I use it to quickly build, test, and deploy models without extensive coding. One of th...
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

No data available
Turbonomic, VMTurbo Operations Manager
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Find out what your peers are saying about DataRobot vs. IBM Turbonomic and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.