Try our new research platform with insights from 80,000+ expert users

DataRobot vs Google Vertex AI 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
13th
Average Rating
8.6
Reviews Sentiment
7.2
Number of Reviews
5
Ranking in other categories
Predictive Analytics (5th), AIOps (16th)
Google Vertex AI
Ranking in AI Development Platforms
2nd
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
10
Ranking in other categories
AI Infrastructure (1st)
 

Mindshare comparison

As of March 2025, in the AI Development Platforms category, the mindshare of DataRobot is 1.3%, up from 1.1% compared to the previous year. The mindshare of Google Vertex AI is 14.9%, down from 19.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

SagarYadav - PeerSpot reviewer
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.
Serge Dahdouh - PeerSpot reviewer
A user-friendly platform that automatizes machine learning techniques with minimal effort
We work with clients who request the implementation of a certain document into a chatbot. Because of the limited knowledge of AI, our task is to link that file to the ML and provide a platform that can work as a customer service. We previously used LangChain Phython, but now it is done through Vertex AI.

Quotes from Members

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

Pros

"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 is highly automated, allowing data scientists to build models easily."
"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."
"We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for training machine learning models. The AI model registry in Vertex AI is crucial for cataloging and managing various versions of the models we develop. When it comes to deploying models, we rely on Google Cloud's AI Prediction service, seamlessly integrating it into our workflow for real-time predictions or streaming. For monitoring and tracking the outcomes of model development, we employ Vertex AI Monitoring, ensuring a comprehensive understanding of the model's performance and results. This integrated approach within Vertex AI provides a unified platform for managing, deploying, and monitoring machine learning models efficiently."
"Google Vertex AI is an out-of-the-box and very easy-to-use solution."
"Vertex comes with inbuilt integration with GCP for data storage."
"Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding."
"The most valuable features of the solution are that it is quite flexible, and some of the services are almost low-code, with no-code services, so it gives agents flexibility to build the use cases according to the operational needs."
"The integration of AutoML features streamlines our machine-learning workflows."
"It provides the most valuable external analytics."
"The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."
 

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."
"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 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 solution is stable, but it is quite slow. Maybe my data is too large, but I think that Google could improve Vertex AI's training time."
"I think the technical documentation is not readily available in the tool."
"The tool's documentation is not good. It is hard."
"Google Vertex AI is good in machine learning and AI, but it lacks optimization."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
"I'm not sure if I have suggestions for improvement."
"I've noticed that using chat activity often presents a broader range of options and insights for a well-constructed question. Improving the knowledge base could be a key aspect for enhancement—expanding the information sources to enhance the generation process."
"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."
 

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 Versa AI offers attractive pricing. With this pricing structure, I can leverage various opportunities to bring value to my business. It's a positive aspect worth considering."
"The price structure is very clear"
"The solution's pricing is moderate."
"I think almost every tool offers a decent discount. In terms of credits or other stuff, every cloud provider provides a good number of incentives to onboard new clients."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
839,422 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Educational Organization
23%
Financial Services Firm
13%
Manufacturing Company
8%
Computer Software Company
8%
Computer Software Company
13%
Financial Services Firm
13%
Manufacturing Company
9%
Retailer
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What needs improvement with DataRobot?
There are some performance issues when it comes to improvements. They also offer storage-related services compared to other tools like Admin, Azure, or AWS. It is easy to plug and play. Third-party...
What is your primary use case for DataRobot?
We work on AI and ML use cases related to technology and IT.
What advice do you have for others considering DataRobot?
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Eve...
What do you like most about Google Vertex AI?
We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for trai...
What is your experience regarding pricing and costs for Google Vertex AI?
They have different pricing models like pay-as-you-go or subscription model, and total cost of ownership. It is comparatively cheaper than Azure.
What needs improvement with Google Vertex AI?
I'm not sure if I have suggestions for improvement. Based on my comparison between the two, Vertex has various additional functionalities that Azure doesn't provide.
 

Overview

 

Sample Customers

Harmoney, Zidisha, ONE Marketing, DonorBureau, Trupanion, Avant
Information Not Available
Find out what your peers are saying about DataRobot vs. Google Vertex AI and other solutions. Updated: January 2025.
839,422 professionals have used our research since 2012.