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Amazon SageMaker vs Google Cloud AI Platform 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)
Google Cloud AI Platform
Ranking in AI Development Platforms
9th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
9
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 Google Cloud AI Platform is 3.6%, down from 6.4% 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.
Vipul-Kumar - PeerSpot reviewer
An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data
I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite.

Quotes from Members

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

Pros

"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."
"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."
"The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use."
"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."
"I appreciate the ease of use in Amazon SageMaker."
"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 most valuable feature of Amazon SageMaker for me is the model deployment service."
"We were able to use the product to automate processes."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."
"The feedback left about these tools was really helpful and informative for us"
"A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick."
"The initial setup is very straightforward."
"The platform's Google Vision API is particularly valuable."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."
 

Cons

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"They could add features such as managing environments, experiment management across those environments, and the integration with training datasets as you go through those experiments."
"Amazon might need to emphasize its capabilities in generative models more effectively."
"I would recommend having more walkthrough videos and articles beyond AWS Skill Builder."
"The product must provide better documentation."
"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."
"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."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"The solution can be improved by simplifying the process to make your own models."
"Customizations are very difficult, and they take time."
"I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite."
"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."
"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."
"The technical support from Google is not very fast. I think it is about a five out of ten even though they have courses online where I can learn a lot, if I really need support, I have to wait a very long time."
"The initial setup was straightforward for me but could be difficult for others."
"It could be more clear, and sometimes there are errors that I don't quite understand."
 

Pricing and Cost Advice

"The support costs are 10% of the Amazon fees and it comes by default."
"SageMaker is worth the money for our use case."
"The solution is relatively cheaper."
"The pricing is comparable."
"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."
"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."
"There is no license required for the solution since you can use it on demand."
"The price of the solution is competitive."
"The solution has an attractive starting program, which costs only 300 USD for a duration of three months. During this period, one can accomplish a lot of work on the solution."
"The pricing is on the expensive side."
"The licenses are cheap."
"For every thousand uses, it is about four and a half euros."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
11%
Manufacturing Company
9%
University
5%
Computer Software Company
15%
Financial Services Firm
11%
Manufacturing Company
9%
University
9%
 

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...
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 Google Cloud AI Platform?
A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up...
What is your experience regarding pricing and costs for Google Cloud AI Platform?
For the most part, the pricing is perfect sinceit grows with the use of my app. In some cases, they could be more specific about the pricing, especially for some AI features.
What is your primary use case for Google Cloud AI Platform?
I use Google Cloud AI Platform due to Firebase and the many APIs that are available with it.
 

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
Carousell
Find out what your peers are saying about Amazon SageMaker vs. Google Cloud AI Platform and other solutions. Updated: July 2025.
865,295 professionals have used our research since 2012.