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 #11 with an average rating of 8.5. Amazon Web Services (AWS) holds a 7.5% 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

6,544 Views
5,235 Comparison Views

91% willing to recommend

IBM Watson Studio

Read 14 IBM Watson Studio reviews

2,088 Views
1,298 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: January 2025).

Buyer's Guide

Amazon SageMaker vs. IBM Watson Studio

January 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

4th

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

11th

Ranking in AI Development Platforms

9th

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.5%, down from 9.9% 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 tool makes our ML model development a bit more efficient because everything is in one environment."

"The most valuable features include the ML operations that allow for designing, deploying, testing, and evaluating models."

"The most valuable feature of Amazon SageMaker for me is the model deployment service."

"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."

"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."

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

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

"SageMaker is a comprehensive platform where I can perform all machine learning activities."

More Amazon SageMaker pros

"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 system's ability to take a look at data, segment it and then use that data very differently."

"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."

"The scalability of IBM Watson Studio is great."

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

"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."

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

More IBM Watson Studio pros

Cons

"The user interface (UI) and user experience (UX) of SageMaker and AWS, in general, need improvement as they are not intuitive and require substantial time to learn how to use specific services."

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

"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."

"The model repository is a concern as models are stored on a bucket and there's an issue with versioning."

"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."

"The solution needs to be cheaper since it now charges per document for extraction."

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

"Amazon might need to emphasize its capabilities in generative models more effectively."

More Amazon SageMaker cons

"Watson Studio would be improved with a clearer path for the deployment of docker images."

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

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

"So a better user interface could be very helpful"

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

"The initial setup was complex."

"I want IBM's technical support team to provide more specific answers to queries."

"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."

More IBM Watson Studio cons

Pricing and Cost Advice

"The pricing is comparable."

"The product is expensive."

"I would rate the solution's price a ten out of ten since it is very high."

"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 solution is relatively cheaper."

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

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."

"Databricks solution is less costly than Amazon SageMaker."

More Amazon SageMaker pricing and cost advice

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

"IBM Watson Studio is an expensive solution."

"IBM Watson Studio is a reasonably priced product"

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

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

14%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

15%

Computer Software Company

12%

Manufacturing Company

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 21% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Dataiku vs Amazon SageMaker

Compared 9% 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 27% of the time

Google Vertex AI vs IBM Watson Studio

Compared 16% of the time

Azure OpenAI vs IBM Watson Studio

Compared 15% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 14% of the time

Darwin 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

February 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

January 2025

Free Report: Amazon SageMaker vs. IBM Watson Studio

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