Google Vertex AI vs IBM Watson Studio comparison

Google and IBM are both solutions in the AI Development Platforms category. Google is ranked #2 with an average rating of 8.3, while IBM is ranked #13 with an average rating of 8.5. Google holds a 10.3% mindshare in AIDP, compared to IBM’s 1.5% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Google Vertex AI

Read 12 Google Vertex AI reviews

7,456 Views
6,710 Comparison Views

100% willing to recommend

IBM Watson Studio

Read 15 IBM Watson Studio reviews

2,091 Views
941 Comparison Views

100% willing to recommend

Google Vertex AI

IBM Watson Studio

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Executive SummaryUpdated on Dec 4, 2024

IBM Watson Studio and Google Vertex AI are tools in the AI sector aimed at data science needs. Google Vertex AI seems to have advantages thanks to its advanced features and integration capabilities, which justify its cost compared to IBM Watson Studio.

Features: IBM Watson Studio provides an integrated environment supporting various data sources and collaborative tools, a necessary feature for enterprise solutions. It includes a comprehensive array of connectors for seamless data importation, and its notebooks simplify data science tasks. Google Vertex AI, meanwhile, offers robust model training capabilities, scalability, and end-to-end AI pipelines. It also excels in automatic machine learning processes and integrates seamlessly with other Google Cloud services.

Room for Improvement: IBM Watson Studio could enhance its user interface to reduce the learning curve for new users and improve its integration speed and efficiency. While its support options are extensive, more streamlined deployment would be beneficial. Google Vertex AI could refine its pricing structure for more cost-effective solutions, expand its in-built library functionalities for broader data set applicability, and enhance user guides for aiding technical onboarding.

Ease of Deployment and Customer Service: IBM Watson Studio provides a flexible cloud deployment model with extensive support options, beneficial for complex needs. Google Vertex AI offers a streamlined deployment process enhanced by Google's infrastructure efficiencies; however, initial technical setup may require expertise. Thus, IBM Watson Studio appeals to businesses needing extensive support, while Google Vertex AI suits those wanting quick integration.

Pricing and ROI: IBM Watson Studio's competitive setup costs and adaptable plans promise high ROI with strong support offerings. In contrast, Google Vertex AI may entail higher initial costs but offers significant ROI through its efficient scaling and advanced AI capabilities. Choosing between them involves balancing immediate costs with long-term value for IBM when budget constraints exist, and opting for Google Vertex AI if high-performance AI solutions are a priority.

To learn more, read our detailed Google Vertex AI vs. IBM Watson Studio Report (Updated: September 2025).

Buyer's Guide

Google Vertex AI vs. IBM Watson Studio

September 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

Google Vertex AI

Ranking in AI Development Platforms

2nd

Average Rating

8.4

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

AI-Agent Builders (3rd)

IBM Watson Studio

Ranking in AI Development Platforms

13th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Science Platforms (12th)

Mindshare comparison

As of October 2025, in the AI Development Platforms category, the mindshare of Google Vertex AI is 10.3%, down from 19.5% compared to the previous year. The mindshare of IBM Watson Studio is 1.5%, down from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms Market Share Distribution
Product	Market Share (%)
Google Vertex AI	10.3%
IBM Watson Studio	1.5%
Other	88.2%

AI Development Platforms

Featured Reviews

Hamada Farag

Technology Consultant at Beta Information Technology

Customization and integration empower diverse AI applications

We are familiar with most Google Cloud services, particularly infrastructure services, storage, compute, AI tools, containerization, GCP containerization, and cloud SQL. We are familiar with approximately eighty percent of Google's services, primarily related to infrastructure, AI, containers, backup, storage, and compute. We are familiar with Gemini AI and Google Vertex AI, and we have completed some exercises and cases with our customers for Google AI. We use automation in machine learning. I work with a team where everyone has specific responsibilities. We have design and development processes in place. Based on my experience, I would rate Google Vertex AI a 9 out of 10.

Read full review

Abilio Duarte

Senior Solutions Architect at Self-employed

A highly robust and well-documented platform that simplifies the complex world of AI

The main challenge lies in visibility and ease of use. Providing training sessions can be immensely helpful in helping users navigate and understand the tool's potential. This approach would empower users to explore and make the most of the tools and technologies at their disposal. Another area where IBM could enhance its offering is by providing more visibility to end users regarding the vast potential that Watson offers.

Read full review

Quotes from Members

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

Pros

"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."

"It provides the most valuable external analytics."

"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 monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."

"Google Vertex AI is an out-of-the-box and very easy-to-use solution."

"The most valuable feature we've found is the model garden, which allows us to deploy and use various models through the provided endpoints easily."

"The support is perfect and fantastic."

"Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding."

More Google Vertex AI pros

"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."

"Watson Studio is the most complete tool for AI projects."

"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."

"In my experience, AutoML is the most valuable feature of IBM Watson Studio."

"Watson Studio is very stable."

"Stability-wise, it is a great tool."

"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."

"The solution is very easy to use."

More IBM Watson Studio pros

Cons

"I'm not sure if I have suggestions for improvement."

"The tool's documentation is not good. It is hard."

"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."

"It takes a considerable amount of time to process, and I understand the technology behind why it takes this long, but this is something that could be reduced."

"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."

"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."

"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."

More Google Vertex AI cons

"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."

"The main challenge lies in visibility and ease of use."

"I think maybe the support is an area where it lacks."

"One area that could be improved is the backup and restoration of the database and the overall database configuration."

"IBM Watson Studio, while powerful, lacks user-friendliness. It is not easy to use, particularly for medium or small enterprises or less experienced staff."

"Some of the solutions are really good solutions but they can be a little too costly for many."

"One area that could be improved is the backup and restoration of the database and the overall database configuration."

"The decision making in their decision making feature is less good than other options."

More IBM Watson Studio cons

Pricing and Cost Advice

"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."

"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."

"IBM Watson Studio is an expensive solution."

"IBM Watson Studio is a reasonably priced product"

"Watson Studio's pricing is reasonable for what you get."

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Top Industries

By visitors reading reviews

Computer Software Company

14%

Financial Services Firm

10%

Manufacturing Company

Educational Organization

Financial Services Firm

12%

Computer Software Company

10%

Manufacturing Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	3
Large Enterprise	6

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	1
Large Enterprise	4

Questions from the Community

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...

See all answers

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.

See all answers

What needs improvement with Google Vertex AI?

Google Vertex AI is one of the best in the market, followed by Azure AI. It can be rated at eight or nine out of ten. It is not completely mature and needs some features and functions. The interfac...

See all answers

What do you like most about IBM Watson Studio?

Stability-wise, it is a great tool.

See all answers

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

IBM Watson Studio is considered rather expensive, with a rating of six or seven. The pricing could be optimized relative to the features and capabilities of the product.

See all answers

What needs improvement with IBM Watson Studio?

IBM Watson Studio, while powerful, lacks user-friendliness. It is not easy to use, particularly for medium or small enterprises or less experienced staff. Another aspect that requires improvement i...

See all answers

Comparisons

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Amazon SageMaker vs Google Vertex AI

Compared 6% of the time

Fireworks AI vs Google Vertex AI

Compared 2% of the time

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Databricks vs IBM Watson Studio

Compared 24% of the time

Azure OpenAI vs IBM Watson Studio

Compared 14% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 13% of the time

KNIME Business Hub vs IBM Watson Studio

Compared 7% of the time

Anaconda Business vs IBM Watson Studio

Compared 6% of the time

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Product Reports

Buyer's Guide

Google Vertex AI

September 2025

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Buyer's Guide

IBM Watson Studio

September 2025

Download IBM Watson Studio product report

Also Known As

No data available

Watson Studio, IBM Data Science Experience, Data Science Experience, DSx

Overview

Build, deploy, and scale ML models faster, with pre-trained and custom tooling within a unified artificial intelligence platform.

Google

IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

IBM

Sample Customers

Information Not Available

GroupM, Accenture, Fifth Third Bank

Buyer's Guide

Google Vertex AI vs. IBM Watson Studio

September 2025

Free Report: Google Vertex AI vs. IBM Watson Studio

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