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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 (2nd)
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 September 2025, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 4.8%, down from 7.2% compared to the previous year. The mindshare of Google Cloud AI Platform is 3.6%, down from 6.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Amazon SageMaker4.8%
Google Cloud AI Platform3.6%
Other91.6%
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

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in 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 these models, making accessing them convenient as needed."
"The technical support of the tool was good."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."
"It's user-friendly for business teams as they can understand many aspects through the AWS interface."
"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 most valuable feature of Amazon SageMaker is SageMaker Studio."
"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."
"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."
"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 solution is able to read 90% of the documents correctly with a 10% error rate."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"I have seen measurable benefits from Google Cloud AI Platform."
"The platform's Google Vision API is particularly valuable."
"The initial setup is very straightforward."
 

Cons

"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."
"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."
"The documentation must be made clearer and more user-friendly."
"The entry point can be a bit difficult. Having all documentation easily accessible on the front page of SageMaker would be a great improvement."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"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."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"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 solution can be improved by simplifying the process to make your own models."
"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."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"The initial setup was straightforward for me but could be difficult for others."
 

Pricing and Cost Advice

"Amazon SageMaker is a very expensive product."
"There is no license required for the solution since you can use it on demand."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
"The pricing could be better, especially for querying. The per-query model feels expensive."
"The solution is relatively cheaper."
"SageMaker is worth the money for our use case."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"Databricks solution is less costly than Amazon SageMaker."
"The licenses are cheap."
"For every thousand uses, it is about four and a half euros."
"The price of the solution is competitive."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
11%
Manufacturing Company
9%
University
6%
Computer Software Company
15%
Financial Services Firm
10%
Manufacturing Company
9%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise11
Large Enterprise16
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 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
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