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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
4th
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
38
Ranking in other categories
Data Science Platforms (2nd)
Google Cloud AI Platform
Ranking in AI Development Platforms
10th
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 March 2026, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 3.6%, down from 5.9% compared to the previous year. The mindshare of Google Cloud AI Platform is 3.3%, down from 4.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
Amazon SageMaker3.6%
Google Cloud AI Platform3.3%
Other93.1%
AI Development Platforms
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
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, 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.
TJ
Owner at Go knowledge
Streamlines app development with dynamic databases and an easy setup
I used Oracle APEX before Google Cloud AI Platform. Oracle APEX is a free tool, except for the Oracle database, which I can only use with it. To have more freedom, I chose Firebase and Google's solutions as it allows me to run it on a hosted server if I want to.

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."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"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."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"I have seen a return on investment, probably a factor of four or five."
"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 these models, making accessing them convenient as needed."
"I appreciate the ease of use in Amazon SageMaker."
"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"The initial setup is very straightforward."
"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 feedback left about these tools was really helpful and informative for us"
"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 platform's Google Vision API is particularly valuable."
"I have seen measurable benefits from Google Cloud AI Platform."
 

Cons

"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."
"The solution requires a lot of data to train the model."
"The main challenge with Amazon SageMaker is the integrations."
"One area where Amazon SageMaker could improve is its pricing. The high costs can drive companies to explore other cloud options. Additionally, while generally good, the updates sometimes come with bugs, and the documentation could be much better. More examples and clearer guidance would be helpful."
"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"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."
"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."
"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 model management on Google Cloud AI Platform could be better."
"The solution can be improved by simplifying the process to make your own models."
"The initial setup was straightforward for me but could be difficult for others."
"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."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
 

Pricing and Cost Advice

"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."
"The pricing is comparable."
"On average, customers pay about $300,000 USD per month."
"The solution is relatively cheaper."
"The support costs are 10% of the Amazon fees and it comes by default."
"There is no license required for the solution since you can use it on demand."
"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."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"For every thousand uses, it is about four and a half euros."
"The pricing is on the expensive side."
"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 price of the solution is competitive."
"The licenses are cheap."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Manufacturing Company
9%
Computer Software Company
9%
University
6%
Computer Software Company
12%
Manufacturing Company
11%
Financial Services Firm
10%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise11
Large Enterprise17
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise2
 

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 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.
What advice do you have for others considering Google Cloud AI Platform?
I have knowledge of it, and I do recommend Google Cloud AI Platform to other people. I would definitely rate the overall solution as an eight out of ten.
 

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: March 2026.
884,873 professionals have used our research since 2012.