DataRobot vs IBM Watson Machine Learning comparison

DataRobot and IBM are both solutions in the AI Development Platforms category. DataRobot is ranked #12 with an average rating of 8.7, while IBM is ranked #13 with an average rating of 8.0. DataRobot holds a 1.4% mindshare in AIDP, compared to IBM’s 1.8% mindshare. Additionally, 100% of DataRobot users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

DataRobot

Read 5 DataRobot reviews

1,231 Views
560 Comparison Views

100% willing to recommend

IBM Watson Machine Learning

Read 7 IBM Watson Machine Learning reviews

1,226 Views
950 Comparison Views

100% willing to recommend

DataRobot

IBM Watson Machine Learning

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 4, 2024

DataRobot and IBM Watson Machine Learning are both prominent in AI and machine learning. DataRobot is often seen as the more user-friendly option, whereas IBM Watson Machine Learning is appreciated for its advanced capabilities and integration options.

Features: DataRobot offers automated machine learning, seamless model management, and a user-friendly AI platform. IBM Watson Machine Learning provides comprehensive analytics, integration with IBM's ecosystem, and supports diverse data formats.

Room for Improvement: DataRobot could enhance its integration capabilities and support for more advanced customization. IBM Watson Machine Learning could improve ease of use and simplify its learning curve. Both products could benefit from faster processing speeds.

Ease of Deployment and Customer Service: DataRobot is recognized for quick deployment and personalized customer support. IBM Watson Machine Learning requires a more complex deployment but is backed by extensive documentation and a knowledgeable support team.

Pricing and ROI: DataRobot provides a clear pricing model advantageous for budget-conscious organizations, offering quicker ROI. IBM Watson Machine Learning might have higher upfront costs but offers better long-term ROI through its scalability and integration capabilities.

To learn more, read our detailed DataRobot vs. IBM Watson Machine Learning Report (Updated: March 2025).

Buyer's Guide

DataRobot vs. IBM Watson Machine Learning

March 2025

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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 AI Development Platforms

12th

Average Rating

8.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Predictive Analytics (5th), AIOps (16th)

IBM Watson Machine Learning

Ranking in AI Development Platforms

13th

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of DataRobot is 1.4%, up from 1.1% compared to the previous year. The mindshare of IBM Watson Machine Learning is 1.8%, down from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

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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Anurag Mayank

Manager at Maruti Suzuki India Limited

A highly efficient solution that delivers the desired results to its users

I had not considered how the solution could be improved because I was focused on how it was helping me to solve my issues. If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use. It would be beneficial to incorporate more AI into the solution.

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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."

"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."

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

"Scalability-wise, I rate the solution ten out of ten."

"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."

"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."

"It is has a lot of good features and we find the image classification very useful."

"It has improved self-service and customer satisfaction."

"The most valuable aspect of the solution's the cost and human labor savings."

"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."

Cons

"There are some performance issues."

"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."

"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."

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

"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."

"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."

"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."

"In future releases, I would like to see a more flexible environment."

"Sometimes training the model is difficult."

"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."

"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."

"The supporting language is limited."

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."

"I've only been using the free tier, but it's quite competitive on a service basis."

"The pricing model is good."

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Top Industries

By visitors reading reviews

Educational Organization

20%

Financial Services Firm

13%

Manufacturing Company

Computer Software Company

17%

Financial Services Firm

11%

Educational Organization

11%

University

10%

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.

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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...

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What do you like most about IBM Watson Machine Learning?

I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive.

See all answers

What is your experience regarding pricing and costs for IBM Watson Machine Learning?

The solution is expensive.

See all answers

What needs improvement with IBM Watson Machine Learning?

Sometimes training the model is difficult. We need to have at least a few different components to evaluate and understand the behavior of different users to have a very, very high accuracy in the m...

See all answers

Comparisons

Amazon SageMaker vs DataRobot

Compared 37% of the time

Datadog vs DataRobot

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs DataRobot

Compared 12% of the time

Altair RapidMiner vs DataRobot

Compared 10% of the time

Alteryx vs DataRobot

Compared 8% of the time

More DataRobot Competitors

Google Cloud AI Platform vs IBM Watson Machine Learning

Compared 67% of the time

Azure OpenAI vs IBM Watson Machine Learning

Compared 12% of the time

TensorFlow vs IBM Watson Machine Learning

Compared 10% of the time

Google Vertex AI vs IBM Watson Machine Learning

Compared 7% of the time

IBM Watson Studio vs IBM Watson Machine Learning

Compared 5% of the time

More IBM Watson Machine Learning Competitors

Product Reports

Buyer's Guide

Predictive Analytics

March 2025

Download DataRobot product report

Buyer's Guide

AI Development Platforms

March 2025

Download IBM Watson Machine Learning product report

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 Watson Machine Learning helps data scientists and developers accelerate AI and machine-learning deployment. With its open, extensible model operation, Watson Machine Learning helps businesses simplify and harness AI at scale across any cloud.

IBM

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant

Information Not Available

Buyer's Guide

DataRobot vs. IBM Watson Machine Learning

March 2025

Free Report: DataRobot vs. IBM Watson Machine Learning

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