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DataRobot vs PyTorch comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 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

DataRobot
Ranking in AI Development Platforms
15th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
6
Ranking in other categories
Predictive Analytics (5th), AIOps (15th), AI Observability (74th), AI Finance & Accounting (6th)
PyTorch
Ranking in AI Development Platforms
9th
Average Rating
8.6
Reviews Sentiment
7.2
Number of Reviews
13
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the AI Development Platforms category, the mindshare of DataRobot is 1.9%, up from 1.3% compared to the previous year. The mindshare of PyTorch is 3.2%, up from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
PyTorch3.2%
DataRobot1.9%
Other94.9%
AI Development Platforms
 

Featured Reviews

Naqash Ahmed - PeerSpot reviewer
Senior Data Reporting Analyst at University of Bradford
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.
Rohan Sharma - PeerSpot reviewer
AI/ML Co-Lead at Developer Student Clubs - GGV
Enabled creation of innovative projects through developer-friendly features
The aspect I like most about PyTorch is that it is really developer-friendly. Developers can constantly create new things, and everyone around the world can use it for free because it's an open-source product. What I personally like is that PyTorch has enabled users to use Apple's M1 chip natively for GPU users. Unlike other libraries using CUDA, PyTorch utilizes Metal Performance Shaders (MPS) to enable GPU usage on M1 chips.

Quotes from Members

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

Pros

"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."
"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."
"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."
"Tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours."
"yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily."
"The product's initial setup phase is easy."
"For me, the product's initial setup phase is easy...For beginners, it is fairly easy to learn."
"We use PyTorch libraries, which are working well. It's very easy."
"PyTorch is developer-friendly, allowing developers to continuously create new projects."
"The tool is very user-friendly."
"PyTorch allows me to build my projects from scratch."
"Its interface is the most valuable. The ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful."
 

Cons

"There are some performance issues."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"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."
"There is a lack of transparency in the models; sometimes it feels like a black box."
"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."
"PyTorch needs improvement in working on ARM-based chips. They have unified memory for GPU and RAM, however, current GPUs used for processing are slow."
"I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."
"The product has certain shortcomings in the automation of machine learning."
"The product has breakdowns when we change the versions a lot."
"The training of the models could be faster."
"The analyzing and latency of compiling could be improved to provide enhanced results."
"PyTorch needs improvement in working on ARM-based chips. They have unified memory for GPU and RAM, however, current GPUs used for processing are slow."
"I would like to see better learning documents."
 

Pricing and Cost Advice

"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 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."
"It is free."
"PyTorch is an open-source solution."
"It is free."
"PyTorch is open source."
"PyTorch is open-sourced."
"The solution is affordable."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
12%
Computer Software Company
10%
Educational Organization
8%
Manufacturing Company
17%
Comms Service Provider
10%
University
10%
Financial Services Firm
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise4
 

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 PyTorch?
I haven't gone for a paid plan yet. I've just been using the free trial or open-source version.
What needs improvement with PyTorch?
PyTorch needs improvement in working on ARM-based chips. Although they have unified memory for GPU and RAM, they are unable to utilize these GPUs for processing efficiently. They take so much time....
 

Comparisons

 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Information Not Available
Find out what your peers are saying about DataRobot vs. PyTorch and other solutions. Updated: December 2025.
881,707 professionals have used our research since 2012.