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Compare Amazon SageMaker and Google Cloud AutoML 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Small-Business (45.5% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Amazon SageMaker
Star Rating
(45)4.3 out of 5
Market Segments
Small-Business (33.3% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Amazon SageMakerGoogle Cloud AutoML
Star Rating
(22)4.1 out of 5
Market Segments
Small-Business (45.5% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Google Cloud AutoMLSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon SageMaker excels in its Managed Service capabilities, with a score of 9.5, making it a preferred choice for businesses looking for a robust managed environment. In contrast, Google Cloud AutoML, while still strong, has a slightly lower score of 8.8 in this area.
- Reviewers mention that SageMaker's Scalability is impressive, scoring 9.0, which allows for seamless handling of large datasets and complex models. Google Cloud AutoML, however, shines even brighter with a score of 9.7, indicating superior scalability options for users.
- G2 users highlight the Ease of Setup in Amazon SageMaker, scoring 8.4, as a significant advantage, especially for small businesses. Conversely, Google Cloud AutoML's score of 7.3 suggests that users may face more challenges during initial setup.
- Users on G2 report that Amazon SageMaker's Quality of Support is commendable, with a score of 8.7, indicating responsive and helpful customer service. In comparison, Google Cloud AutoML's support, scoring 7.6, may not meet the same level of user satisfaction.
- Reviewers mention that SageMaker's Data Ingestion & Wrangling capabilities, scoring 8.1, are effective but could be improved. Google Cloud AutoML, while not explicitly rated in this area, is often praised for its user-friendly data handling features, suggesting a more intuitive experience.
- Users say that both platforms offer strong Machine/Deep Learning Services, but Google Cloud AutoML stands out with higher scores in specific areas like Natural Language Understanding (9.2) and Computer Vision (9.6), indicating a broader range of pre-built models that cater to diverse user needs.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableGoogle Cloud AutoML
No pricing availableFree Trial
Amazon SageMaker
No trial information availableGoogle Cloud AutoML
No trial information availableRatings
Meets Requirements
8.6
37
8.6
14
Ease of Use
8.4
38
8.6
14
Ease of Setup
8.5
25
7.4
11
Ease of Admin
8.4
20
7.9
12
Quality of Support
8.6
33
7.5
14
Has the product been a good partner in doing business?
9.2
20
8.3
11
Product Direction (% positive)
9.0
36
8.9
11
Features by Category
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Operations
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
8.2
19
Not enough data
Model Development
8.7
29
Not enough data
8.2
28
Not enough data
8.3
33
Not enough data
8.9
33
Not enough data
Model Development
8.4
19
Not enough data
Machine/Deep Learning Services
8.9
26
Not enough data
9.1
28
Not enough data
8.9
25
Not enough data
9.0
28
Not enough data
Machine/Deep Learning Services
9.2
17
Not enough data
9.2
18
Not enough data
Deployment
8.6
32
Not enough data
8.6
32
Not enough data
9.0
31
Not enough data
Generative AI
8.6
6
Not enough data
9.2
6
Not enough data
8.3
5
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Amazon SageMaker and Google Cloud AutoML are categorized as Data Science and Machine Learning Platforms and Low-Code Machine Learning Platforms
Unique Categories
Amazon SageMaker is categorized as MLOps Platforms and Generative AI Infrastructure
Google Cloud AutoML has no unique categories
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Google Cloud AutoML
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
19.0%
Computer Software
16.7%
Marketing and Advertising
4.8%
Internet
4.8%
Hospital & Health Care
4.8%
Other
50.0%
Research
13.6%
Information Technology and Services
13.6%
Computer Software
9.1%
Program Development
4.5%
Pharmaceuticals
4.5%
Other
54.5%
Alternatives
Discussions
What is the best way to integrate Sagemaker models with Kubernetes?
1 Comment
VJ
https://aws.amazon.com/blogs/machine-learning/introducing-amazon-sagemaker-operators-for-kubernetes/Read more
How do i make this platform reach to most of my developers?
1 Comment
VJ
you can manage the access via IAM users and roles and give them access as per their need, Sagemaker by default has all the basic AWS feature and you can...Read more
Amazon SageMaker has no more discussions with answers
Google Cloud AutoML has no discussions with answers
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