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 8.4. Amazon Web Services (AWS) holds a 6.9% mindshare in Data Science Platforms, compared to IBM’s 2.0% 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 37 Amazon SageMaker reviews

5,661 Views
4,573 Comparison Views

91% willing to recommend

IBM Watson Studio

Read 15 IBM Watson Studio reviews

1,946 Views
1,192 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: April 2025).

Buyer's Guide

Amazon SageMaker vs. IBM Watson Studio

April 2025

Download the complete report

Helped 851,491 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:

ROI

Sentiment score

7.3

Amazon SageMaker delivers high ROI by reducing costs and time, often providing returns multiple times the initial investment.

Sentiment score

7.0

Organizations saw positive ROI from IBM Watson Studio due to improved efficiency, scalability, sales, and reduced staffing needs.

The return on investment varies by use case and offers significant value in revenue increases and cost saving capabilities, especially in real time fraud detection and targeted advertisements.

reviewer1363764

Senior Solutions Architect at Amazon

For more quotes and insights, download the Amazon SageMaker report

The product offers a significant return on investment through its scalability and integration capabilities.

Willie Torres

Process Automation Lead at CONDIACTOR

My customers have seen returns on investment through increased efficiency, automated calculations, improved accuracy in pricing, and reduced staffing needs due to the automation.

Altan_Atabarut

Director, Channel and Alliances at Akinon

For more quotes and insights, download the IBM Watson Studio report

Customer Service

Sentiment score

7.2

Amazon SageMaker support is generally praised, but service quality varies; premium customers receive better, more responsive assistance.

Sentiment score

7.2

IBM Watson Studio customer service is praised for efficiency and responsiveness, though support quality varies by subscription plan and community resources.

The technical support from AWS is excellent.

Hemant Paralkar

Lead Consultant at Saama

The response time is generally swift, usually within seven to eight hours.

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

The support is very good with well-trained engineers.

reviewer1363764

Senior Solutions Architect at Amazon

For more quotes and insights, download the Amazon SageMaker report

The support quality depends on the SLA or the contract terms.

Willie Torres

Process Automation Lead at CONDIACTOR

The community access is weak, which limits the ability to engage in discussions and find documentation and examples of similar cases effectively.

Altan_Atabarut

Director, Channel and Alliances at Akinon

For more quotes and insights, download the IBM Watson Studio report

Scalability Issues

Sentiment score

7.6

Amazon SageMaker offers scalability and adaptability across enterprises, but GPU limitations and user skills impact its overall efficiency.

Sentiment score

7.5

IBM Watson Studio is scalable with excellent integration, but its resource intensity may increase costs for extensive scaling.

It works very well with large data sets from one terabyte to fifty terabytes.

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

The availability of GPU instances can be a challenge, requiring proper planning.

reviewer1363764

Senior Solutions Architect at Amazon

Amazon SageMaker is scalable and works well from an infrastructure perspective.

Hemant Paralkar

Lead Consultant at Saama

For more quotes and insights, download the Amazon SageMaker report

Watson Studio is very scalable.

Willie Torres

Process Automation Lead at CONDIACTOR

I rate IBM Watson Studio seven out of ten for scalability because while it scales, it requires significant resources to do so, making it expensive compared to some competitors.

Altan_Atabarut

Director, Channel and Alliances at Akinon

For more quotes and insights, download the IBM Watson Studio report

Stability Issues

Sentiment score

7.8

Amazon SageMaker is stable with high reliability, especially when properly configured, and minor glitches do not significantly impact performance.

Sentiment score

7.4

IBM Watson Studio is praised for stability and reliability, comparable to or better than competitors, with effective optimization for large tasks.

There are issues, but they are easily detectable and fixable, with smooth error handling.

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

I rate the stability of Amazon SageMaker between seven and eight.

Hemant Paralkar

Lead Consultant at Saama

For more quotes and insights, download the Amazon SageMaker report

Expertise in optimization is necessary to manage such issues effectively.

Altan_Atabarut

Director, Channel and Alliances at Akinon

For more quotes and insights, download the IBM Watson Studio report

Room For Improvement

Users seek better pricing, interface, integration, documentation, AI, dataset support, security, serverless options, and AWS collaboration.

IBM Watson Studio needs a more intuitive interface, better support, and reduced setup complexity for wider adoption.

Both SageMaker and Lambda are powerful tools, and combining their capabilities could be beneficial.

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background.

Hemant Paralkar

Lead Consultant at Saama

Integration of the latest machine learning models like the new Amazon LLM models could enhance its capabilities.

reviewer1363764

Senior Solutions Architect at Amazon

For more quotes and insights, download the Amazon SageMaker report

IBM should work on optimizing the user interface and enhancing the product's accessibility for medium and small enterprises.

Altan_Atabarut

Director, Channel and Alliances at Akinon

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

Willie Torres

Process Automation Lead at CONDIACTOR

For more quotes and insights, download the IBM Watson Studio report

Setup Cost

Amazon SageMaker offers flexible, competitive pricing but can be costly, with value varying by user, plus available discounts.

IBM Watson Studio's pricing varies, offering a free light edition, yet considered expensive by some, especially in Africa.

The cost for small to medium instances is not very high.

Syed Muhammad Noman Akhtar

AWS & Azure Engineer at a media company with 11-50 employees

The pricing can be up to eight or nine out of ten, making it more expensive than some cloud alternatives yet more economical than on-premises setups.

reviewer1363764

Senior Solutions Architect at Amazon

For a single user, prices might be high yet could be cheaper for user-managed services compared to AWS-managed services.

Hemant Paralkar

Lead Consultant at Saama

For more quotes and insights, download the Amazon SageMaker report

IBM Watson Studio is considered rather expensive, with a rating of six or seven.

Altan_Atabarut

Director, Channel and Alliances at Akinon

For more quotes and insights, download the IBM Watson Studio report

Valuable Features

Amazon SageMaker offers comprehensive tools for end-to-end machine learning, including model deployment, scalability, and user-friendly features.

IBM Watson Studio excels in automation, predictive analytics, and integration, offering comprehensive AI capabilities for diverse data-driven tasks.

SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project.

Syed Muhammad Noman Akhtar

AWS & Azure Engineer at a media company with 11-50 employees

SageMaker is fully managed, offers high availability, flexibility with TensorFlow, PyTorch, and MXNet, and comes with pre-trained algorithms for forecasting, anomaly detection, and more.

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

These features facilitate rapid development and deployment of AI applications.

reviewer1363764

Senior Solutions Architect at Amazon

For more quotes and insights, download the Amazon SageMaker report

This capability saves a significant amount of time by automating processes that typically involve manual work, such as data cleaning, feature engineering, and predictive analytics.

Altan_Atabarut

Director, Channel and Alliances at Akinon

It integrates well with other platforms and offers good scalability.

Willie Torres

Process Automation Lead at CONDIACTOR

For more quotes and insights, download the IBM Watson Studio report

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

11th

Ranking in AI Development Platforms

10th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.9%, down from 9.7% compared to the previous year. The mindshare of IBM Watson Studio is 2.0%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

Create innovative assistants with seamless data integration for large-scale projects

The various integration options available in Amazon SageMaker ( /products/amazon-sagemaker-reviews ), such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue ( /products/aws-glue-reviews ) integrate well for data transformations. The Databricks ( /products/databricks-reviews ) integration aids data scientists and engineers. SageMaker is fully managed, offers high availability, flexibility with TensorFlow ( /products/tensorflow-reviews ), PyTorch ( /products/pytorch-reviews ), and MXNet ( /products/mxnet-reviews ), and comes with pre-trained algorithms for forecasting, anomaly detection, and more.

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

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

11%

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?

The pricing is high, around an eight. However, SageMaker offers free trials for the first two months, allowing users to determine which features they need. It is considered value for money given it...

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 15% of the time

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Compared 12% of the time

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Compared 11% of the time

Google Vertex AI vs Amazon SageMaker

Compared 8% 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 27% of the time

Microsoft Azure Machine Learning Studio vs IBM Watson Studio

Compared 14% of the time

Azure OpenAI vs IBM Watson Studio

Compared 13% of the time

Google Vertex AI vs IBM Watson Studio

Compared 12% of the time

Amazon Comprehend vs IBM Watson Studio

Compared 4% of the time

More IBM Watson Studio Competitors

Product Reports

Buyer's Guide

Amazon SageMaker

May 2025

Download Amazon SageMaker product report

Buyer's Guide

IBM Watson Studio

May 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

April 2025

Free Report: Amazon SageMaker vs. IBM Watson Studio

Find out what your peers are saying about Amazon SageMaker vs. IBM Watson Studio and other solutions. Updated: April 2025.

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