Amazon SageMaker vs IBM Watson Studio comparison

Amazon Web Services (AWS) and IBM are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #3 with an average rating of 8.0, while IBM is ranked #12 with an average rating of 8.4. Amazon Web Services (AWS) holds a 7.3% mindshare in Data Science Platforms, compared to IBM’s 1.9% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Amazon SageMaker

Read 36 Amazon SageMaker reviews

6,112 Views
4,892 Comparison Views

91% willing to recommend

IBM Watson Studio

Read 14 IBM Watson Studio reviews

1,997 Views
1,233 Comparison Views

100% willing to recommend

Amazon SageMaker

IBM Watson Studio

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 4, 2024

IBM Watson Studio and Amazon SageMaker are both designed for machine learning model development and deployment. IBM Watson Studio appears to have an advantage in pricing and customer support, while Amazon SageMaker excels in its comprehensive feature set.

Features: IBM Watson Studio offers a collaborative environment with intuitive tools, AutoAI technology for model selection, and easy data integration. Amazon SageMaker provides comprehensive services for model building, advanced algorithms, seamless AWS integration, and features like the SageMaker Studio and AutoPilot for simplified model management.

Room for Improvement: IBM Watson Studio could improve on integration with non-IBM platforms, offer more advanced features for large datasets, and enhance scalability for extensive applications. Amazon SageMaker might enhance its user interface for newcomers, refine its pricing transparency, and improve customer service personalization.

Ease of Deployment and Customer Service: IBM Watson Studio offers a straightforward deployment process and superior customer service, with cloud-based and hybrid solutions that easily meet diverse deployment needs. Amazon SageMaker leverages AWS’s vast cloud infrastructure for flexible deployments but lacks the personal touch in customer service that some users prefer.

Pricing and ROI: IBM Watson Studio is recognized for competitive pricing and good ROI with low setup costs, attractive for budget-constrained organizations. Amazon SageMaker justifies its higher cost with features and integration that offer greater ROI potential for larger enterprises in need of scalable machine learning solutions.

To learn more, read our detailed Amazon SageMaker vs. IBM Watson Studio Report (Updated: March 2025).

Buyer's Guide

Amazon SageMaker vs. IBM Watson Studio

March 2025

Download the complete report

Helped 842,767 peers since 2012

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

Amazon SageMaker

Ranking in Data Science Platforms

3rd

Ranking in AI Development Platforms

5th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM Watson Studio

Ranking in Data Science Platforms

12th

Ranking in AI Development Platforms

10th

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.3%, down from 9.8% compared to the previous year. The mindshare of IBM Watson Studio is 1.9%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Hemant Paralkar

Lead Consultant at Saama

Improves team collaboration with advanced feature sharing but needs a better user experience

Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.

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

"We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed."

"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."

"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."

"The product aggregates everything we need to build and deploy machine learning models in one place."

"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."

"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."

"The few projects we have done have been promising."

"The evolution from SageMaker Classic to SageMaker Studio, particularly the UI part of Studio, is commendable."

More Amazon SageMaker pros

"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."

"Watson Studio is very stable."

"It is a very stable and reliable solution."

"It has greatly improved the performance because it is standardized across the company."

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

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

"It is a stable, reliable product."

"The solution is very easy to use."

More IBM Watson Studio pros

Cons

"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."

"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."

"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."

"The entry point can be a bit difficult. Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."

"Lacking in some machine learning pipelines."

"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."

More Amazon SageMaker 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."

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

"The initial setup was complex."

"The solution's interface is very slow at times."

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

"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."

"We would like to see it more web-based with more functionality."

"So a better user interface could be very helpful"

More IBM Watson Studio cons

Pricing and Cost Advice

"The support costs are 10% of the Amazon fees and it comes by default."

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."

"The product is expensive."

"The tool's pricing is reasonable."

"There is no license required for the solution since you can use it on demand."

"The pricing could be better, especially for querying. The per-query model feels expensive."

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

"The solution is relatively cheaper."

More Amazon SageMaker pricing and cost advice

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

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

"IBM Watson Studio is a reasonably priced product"

"IBM Watson Studio is an expensive solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

13%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

15%

Computer Software Company

12%

Manufacturing Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

See all answers

What do you like most about Amazon SageMaker?

We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...

See all answers

What is your experience regarding pricing and costs for Amazon SageMaker?

Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.

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?

The pricing of Watson Studio is justified by the benefits and power it offers.

See all answers

What needs improvement with IBM Watson Studio?

One area that could be improved is the backup and restoration of the database and the overall database configuration. There were also challenges with programming the network extension in the last p...

See all answers

Comparisons

Databricks vs Amazon SageMaker

Compared 17% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Dataiku vs Amazon SageMaker

Compared 10% of the time

Google Vertex AI vs Amazon SageMaker

Compared 9% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

More Amazon SageMaker Competitors

Databricks vs IBM Watson Studio

Compared 28% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 16% of the time

Azure OpenAI vs IBM Watson Studio

Compared 15% of the time

Google Vertex AI vs IBM Watson Studio

Compared 15% of the time

IBM Watson Machine Learning vs IBM Watson Studio

Compared 3% of the time

More IBM Watson Studio Competitors

Product Reports

Buyer's Guide

Amazon SageMaker

March 2025

Download Amazon SageMaker product report

Buyer's Guide

IBM Watson Studio

March 2025

Download IBM Watson Studio product report

Also Known As

AWS SageMaker, SageMaker

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

Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Amazon Web Services (AWS)

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

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

GroupM, Accenture, Fifth Third Bank

Buyer's Guide

Amazon SageMaker vs. IBM Watson Studio

March 2025

Free Report: Amazon SageMaker vs. IBM Watson Studio

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