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

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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

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

"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."

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

"They offer insights into everyone making calls in my organization."

"The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases."

"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."

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

"The support is very good with well-trained engineers whose training curriculum is rigorous."

"The most valuable feature of Amazon SageMaker is SageMaker Studio."

More Amazon SageMaker pros

"The scalability of IBM Watson Studio is great."

"IBM Watson Studio consistently automates across channels."

"Watson Studio is very stable."

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

"It is a very stable and reliable solution."

"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 the most complete tool for AI projects."

"It has a lot of data connectors, which is extremely helpful."

More IBM Watson Studio pros

Cons

"The documentation must be made clearer and more user-friendly."

"The solution is complex to use."

"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."

"One area for improvement is the pricing, which can be quite high."

"For any cloud provider, the cost has to be substantially reduced, especially in the case of Amazon SageMaker, which is extremely expensive for huge workloads."

"The product must provide better documentation."

"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."

"Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker."

More Amazon SageMaker cons

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

"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."

"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."

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

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

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

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

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

More IBM Watson Studio cons

Pricing and Cost Advice

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

"The tool's pricing is reasonable."

"The pricing is comparable."

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

"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."

"Amazon SageMaker is a very expensive product."

"SageMaker is worth the money for our use case."

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."

"IBM Watson Studio is a reasonably priced product"

"IBM Watson Studio is an expensive solution."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Educational Organization

13%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

15%

Computer Software Company

12%

Manufacturing Company

10%

Educational Organization

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

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Compared 17% of the time

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Compared 12% of the time

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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

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Databricks vs IBM Watson Studio

Compared 26% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 15% of the time

Azure OpenAI vs IBM Watson Studio

Compared 14% of the time

Google Vertex AI vs IBM Watson Studio

Compared 14% of the time

Alteryx 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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