DataRobot vs IBM Turbonomic comparison

DataRobot and IBM are both solutions in the AIOps category. DataRobot is ranked #15 with an average rating of 8.7, while IBM is ranked #5 with an average rating of 8.5. DataRobot holds a 0.6% mindshare in AIOP, compared to IBM’s 0.4% mindshare. Additionally, 100% of DataRobot users are willing to recommend the solution, compared to 98% of IBM users who would recommend it.

DataRobot

Read 5 DataRobot reviews

233 Views
12 Comparison Views

100% willing to recommend

IBM Turbonomic

Read 205 IBM Turbonomic reviews

180 Views
7 Comparison Views

98% willing to recommend

DataRobot

IBM Turbonomic

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Executive Summary

We performed a comparison between DataRobot and IBM Turbonomic based on real PeerSpot user reviews.

Find out in this report how the two AIOps solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed DataRobot vs. IBM Turbonomic Report (Updated: April 2025).

Buyer's Guide

DataRobot vs. IBM Turbonomic

April 2025

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Helped 857,028 peers since 2012

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

DataRobot

Ranking in AIOps

15th

Average Rating

8.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Predictive Analytics (5th), AI Development Platforms (13th)

IBM Turbonomic

Ranking in AIOps

5th

Average Rating

8.8

Reviews Sentiment

7.4

Number of Reviews

205

Ranking in other categories

Cloud Migration (4th), Cloud Management (4th), Virtualization Management Tools (2nd), IT Financial Management (1st), IT Operations Analytics (4th), Cloud Analytics (1st), Cloud Cost Management (1st)

Mindshare comparison

As of June 2025, in the AIOps category, the mindshare of DataRobot is 0.6%, up from 0.2% compared to the previous year. The mindshare of IBM Turbonomic is 0.4%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AIOps

Featured Reviews

SagarYadav

Staff Specialist Data Scientist at BMC Software, Inc.

Automating model comparison speeds up development and reduces timelines

DataRobot is equipped with a GUI-based approach that simplifies the process of feature engineering and model training. It provides AutoML capabilities, which allow for comparing thousands of models and selecting the best-suited one based on business requirements. By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.

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Dan Ambrose

Infrastructure Engineer 4 at Hyland

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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Quotes from Members

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

Pros

"DataRobot can be easy to use."

"By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month."

"DataRobot is highly automated, allowing data scientists to build models easily."

"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."

"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."

"We have VM placement in Automated mode and currently have all other metrics in Recommend mode."

"The biggest value I'm getting out of VMTurbo right now is the complete hands-off management of equalizing the usage in my data center."

"I like Turbonomic's built-in reporting. It provides a ton of information out of the box, so I don't have to build panels for the monthly summaries and other reports I need to present to management. We get better performance and bottleneck reporting from this than we do from our older EMC software."

"Before implementing Turbonomic, we had difficulty reaching a consensus about VM placement and sizing. Everybody's opinion was wrong, including mine. The application developers, implementers, and infrastructure team could never decide the appropriate size of a virtual machine. I always made the machines small, and they always made them too big. We were both probably wrong."

"My favorite part of the solution is the automation scheduling. Being able to choose when actions happen, and how they happen..."

"Using this product helps us to reduce performance risk because it shows us where resources are needed but not yet allocated."

"The recommendation of the family types is a huge help because it has saved us a lot of money. We use it primarily for that. Another thing that Turbonomic provides us with is a single platform that manages the full application stack and that's something I really like."

"The ability to monitor and automate both the right-sizing of VMs as well as to automate the vMotion of VMs across ESXi hosts."

More IBM Turbonomic pros

Cons

"There are some performance issues."

"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."

"DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality."

"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."

"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."

"Recovering resources when they're not needed is not as optimized as it could be."

"Since the introduction of a HTML 5 based interface, our main - but minor - criticism of a less than intuitive operation managers' GUI would be the area of improvement."

"While the product is fairly intuitive and easy to use once you learn it, it can be quite daunting until you have undergone a bit of training."

"The old interface was not the clearest UI in some areas, and could be quite intimidating when first using the tool."

"The deployment process is a little tricky. It wasn't hard for me because I have pretty in-depth knowledge of Kubernetes, and their software runs on Kubernetes. To deploy it or upgrade it, you have to be able to follow steps and use the Kubernetes command line, or you'll need someone to come in and do it for you."

"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."

"The GUI and policy creation have room for improvement. There should be a better view of some of the numbers that are provided and easier to access. And policy creation should have it easier to identify groups."

"The implementation could be enhanced."

More IBM Turbonomic cons

Pricing and Cost Advice

"The price of DataRobot is good because if you take the price of the solution which is approximately $65,000, it is less than a data scientist. There are very few data scientists available."

"We dropped the plan to use DataRobot, because we found the pricing to be on the higher sise. We liked DataRobot a lot, but due to the pricing, we dropped that idea."

"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."

"It was an annual buy-in. You basically purchase it based on your host type stuff. The buy-in was about 20K, and the annual maintenance is about $3,000 a year."

"IBM Turbonomic is an investment that we believe will deliver positive returns."

"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."

"The pricing and licensing are fair. We purchase based on benchmark pricing, which we have been able to get. There are no surprise charges nor hidden fees."

"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."

"Contact the Turbonomic sales team, explain your needs and what you're looking to monitor. They will get a pre-sales SE on the phone and together work up a very accurate quote."

"I don't know the current prices, but I like how the licensing is based on the number of instances instead of sockets, clusters, or cores. We have some VMs that are so heavy I can only fit four on one server. It's not cost-effective if we have to pay more for those. When I move around a VM SQL box with 30 cores and a half-terabyte of RAM, I'm not paying for an entire socket and cores where people assume you have at least 10 or 20 VMs on that socket for that pricing."

More IBM Turbonomic pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Educational Organization

13%

Manufacturing Company

Computer Software Company

Financial Services Firm

14%

Computer Software Company

13%

Manufacturing Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What needs improvement with DataRobot?

DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality.

See all answers

What is your primary use case for DataRobot?

In our day-to-day use, I utilize DataRobot to speed up our development process through its GUI capability. Once I set up our connection with a back-end data set, whatever the project I work on next...

See all answers

What advice do you have for others considering DataRobot?

I would recommend DataRobot because if there is something not included in the UI, I have the freedom to use its Python API, which extends the capability for different use cases. Additionally, I wou...

See all answers

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 ...

See all answers

What needs improvement with Turbonomic?

The implementation could be enhanced.

See all answers

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...

See all answers

Comparisons

Amazon SageMaker vs DataRobot

Compared 37% of the time

Microsoft Azure Machine Learning Studio vs DataRobot

Compared 10% of the time

Datadog vs DataRobot

Compared 8% of the time

Altair RapidMiner vs DataRobot

Compared 8% of the time

Alteryx vs DataRobot

Compared 7% of the time

More DataRobot Competitors

VMware Aria Operations vs IBM Turbonomic

Compared 16% of the time

Azure Cost Management vs IBM Turbonomic

Compared 11% of the time

VMware vSphere vs IBM Turbonomic

Compared 7% of the time

Cloudability vs IBM Turbonomic

Compared 6% of the time

VMware Aria Automation vs IBM Turbonomic

Compared 5% of the time

More IBM Turbonomic Competitors

Product Reports

Buyer's Guide

Predictive Analytics

May 2025

Download DataRobot product report

Buyer's Guide

IBM Turbonomic

June 2025

Download IBM Turbonomic product report

Also Known As

No data available

Turbonomic, VMTurbo Operations Manager

Interactive Demo

Demo not available

DataRobot

IBM

Overview

DataRobot captures the knowledge, experience and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users to build and deploy highly accurate machine learning models in a fraction of the time.

DataRobot

IBM Turbonomic offers automation, planning, and right-sizing recommendations to streamline resource management, improve efficiencies, and optimize costs across virtualized environments and cloud platforms.

IBM Turbonomic is valued for its capability to optimize resource allocation and monitor virtual environments efficiently. It facilitates automated decision-making in VM sizing, load balancing, and cost optimization for both on-premises and cloud deployments. Users can leverage insights for workload placement, ensure peak performance assurance, and effectively right-size across VMware and Azure. The ongoing transition to HTML5 aims to improve visual and navigational ease, while expanded reporting features are anticipated. Opportunities for improved training, documentation, and integrations enhance platform usability and functionality.

What Are the Key Features?

Automation: Streamlines resource allocation and VM management.
Planning Tools: Supports capacity management and growth projections.
Right-Sizing: Optimizes VM configurations for efficient resource use.
Customizable Dashboards: Provides quick insights into environment health.
Reporting Capabilities: Offers valuable data for informed decision-making.
Cloud Integration: Ensures cost-effective resource utilization.

What Benefits Should Be Looked For?

Performance Enhancement: Improves application performance efficiency.
Cost Reduction: Minimizes operational expenses through optimizations.
Infrastructure Efficiency: Maximizes use of IT infrastructure resources.

In finance, IBM Turbonomic aids in maintaining platform efficiency during market fluctuations. Healthcare organizations leverage its capability for resource optimization during high-demand periods to enhance patient care support. Retailers use it for planning in peak seasons, ensuring resources align with fluctuating demand to maintain performance continuity.

IBM

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.

Buyer's Guide

DataRobot vs. IBM Turbonomic

April 2025

Free Report: DataRobot vs. IBM Turbonomic

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