Try our new research platform with insights from 80,000+ expert users

Amazon SageMaker vs IBM Watson Machine Learning comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024

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 AI Development Platforms
5th
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
38
Ranking in other categories
Data Science Platforms (3rd)
IBM Watson Machine Learning
Ranking in AI Development Platforms
13th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
7
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 5.0%, down from 7.4% compared to the previous year. The mindshare of IBM Watson Machine Learning is 1.9%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
Create innovative assistants with seamless data integration for large-scale projects
The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue integrate well for data transformations. The Databricks integration aids data scientists and engineers. 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.
Anurag Mayank - PeerSpot reviewer
A highly efficient solution that delivers the desired results to its users
I had not considered how the solution could be improved because I was focused on how it was helping me to solve my issues. If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use. It would be beneficial to incorporate more AI into the solution.

Quotes from Members

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

Pros

"We were able to use the product to automate processes."
"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."
"The most tool's valuable feature, in my experience, is hyperparameter tuning. It allows us to test different parameters for the same model in parallel, which helps us quickly identify the configuration that yields the highest accuracy. This parallel computing capability saves us a lot of time."
"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"The support is very good with well-trained engineers whose training curriculum is rigorous."
"We've had no problems with SageMaker's stability."
"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."
"It has improved self-service and customer satisfaction."
"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."
"It is has a lot of good features and we find the image classification very useful."
"Scalability-wise, I rate the solution ten out of ten."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"The most valuable aspect of the solution's the cost and human labor savings."
 

Cons

"The main challenge with Amazon SageMaker is the integrations."
"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."
"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."
"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 entry point can be a bit difficult. Having all documentation easily accessible on the front page of SageMaker would be a great improvement."
"The solution needs to be cheaper since it now charges per document for extraction."
"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."
"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
"The supporting language is limited."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"Sometimes training the model is difficult."
"In future releases, I would like to see a more flexible environment."
 

Pricing and Cost Advice

"Amazon SageMaker is a very expensive product."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
"The pricing is comparable."
"Databricks solution is less costly than Amazon SageMaker."
"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 pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."
"I've only been using the free tier, but it's quite competitive on a service basis."
"The pricing model is good."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
865,384 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
11%
Manufacturing Company
9%
University
5%
University
13%
Computer Software Company
13%
Financial Services Firm
11%
Educational Organization
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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...
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...
What is your experience regarding pricing and costs for Amazon SageMaker?
If you manage it effectively, their pricing is reasonable. It's similar to anything in the cloud; if you don't manage it properly, it can be expensive, but if you do, it's fine.
What do you like most about IBM Watson Machine Learning?
I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive.
What needs improvement with IBM Watson Machine Learning?
Sometimes training the model is difficult. We need to have at least a few different components to evaluate and understand the behavior of different users to have a very, very high accuracy in the m...
 

Also Known As

AWS SageMaker, SageMaker
No data available
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
Information Not Available
Find out what your peers are saying about Amazon SageMaker vs. IBM Watson Machine Learning and other solutions. Updated: July 2025.
865,384 professionals have used our research since 2012.