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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 makes our ML model development a bit more efficient because everything is in one environment."
"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."
"The support is very good with well-trained engineers whose training curriculum is rigorous."
"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"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."
"They offer insights into everyone making calls in my organization."
"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"The platform's Google Vision API is particularly valuable."
"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."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"The feedback left about these tools was really helpful and informative for us"
"The initial setup is very straightforward."
"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."
 

Cons

"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."
"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."
"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."
"The main challenge with Amazon SageMaker is the integrations."
"The solution is complex to use."
"The platform could be more accessible to users with basic coding skills, making it more intuitive and easier for beginners to use comfortably."
"SageMaker would be improved with the addition of reporting services."
"There are other better solutions for large data, such as Databricks."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"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."
"Customizations are very difficult, and they take time."
"The initial setup was straightforward for me but could be difficult for others."
"The model management on Google Cloud AI Platform could be better."
"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."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
 

Pricing and Cost Advice

"The pricing is comparable."
"Databricks solution is less costly than Amazon SageMaker."
"There is no license required for the solution since you can use it on demand."
"Amazon SageMaker is a very expensive product."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"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."
"I would rate the solution's price a ten out of ten since it is very high."
"SageMaker is worth the money for our use case."
"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."
"For every thousand uses, it is about four and a half euros."
"The pricing is on the expensive side."
"The licenses are cheap."
"The price of the solution is competitive."
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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.