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DataRobot vs Google Cloud AI Platform 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 (66th), AI Finance & Accounting (4th)
Google Cloud AI Platform
Ranking in AI Development Platforms
10th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
9
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the AI Development Platforms category, the mindshare of DataRobot is 1.8%, up from 1.3% compared to the previous year. The mindshare of Google Cloud AI Platform is 3.2%, down from 5.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Google Cloud AI Platform3.2%
DataRobot1.8%
Other95.0%
AI Development Platforms
 

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.
TJ
Owner at Go knowledge
Streamlines app development with dynamic databases and an easy setup
I used Oracle APEX before Google Cloud AI Platform. Oracle APEX is a free tool, except for the Oracle database, which I can only use with it. To have more freedom, I chose Firebase and Google's solutions as it allows me to run it on a hosted server if I want to.

Quotes from Members

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

Pros

"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."
"DataRobot can be easy to use."
"Tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours."
"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."
"The platform's Google Vision API is particularly valuable."
"The feedback left about these tools was really helpful and informative for us"
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."
"The initial setup is very straightforward."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."
 

Cons

"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."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
"There are some performance issues."
"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."
"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."
"The solution can be improved by simplifying the process to make your own models."
"The technical support from Google is not very fast. I think it is about a five out of ten even though they have courses online where I can learn a lot, if I really need support, I have to wait a very long time."
"The initial setup was straightforward for me but could be difficult for others."
"Customizations are very difficult, and they take time."
"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."
"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"It could be more clear, and sometimes there are errors that I don't quite understand."
 

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 licenses are cheap."
"The price of the solution is competitive."
"The pricing is on the expensive side."
"For every thousand uses, it is about four and a half euros."
"The solution has an attractive starting program, which costs only 300 USD for a duration of three months. During this period, one can accomplish a lot of work on the solution."
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Top Industries

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

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise2
 

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 Google Cloud AI Platform?
For the most part, the pricing is perfect sinceit grows with the use of my app. In some cases, they could be more specific about the pricing, especially for some AI features.
What is your primary use case for Google Cloud AI Platform?
I use Google Cloud AI Platform due to Firebase and the many APIs that are available with it.
What advice do you have for others considering Google Cloud AI Platform?
I have knowledge of it, and I do recommend Google Cloud AI Platform to other people. I would definitely rate the overall solution as an eight out of ten.
 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Carousell
Find out what your peers are saying about DataRobot vs. Google Cloud AI Platform and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.