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Compare Amazon SageMaker and Red Hat OpenShift Data Science 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Mid-Market (44.0% 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 SageMakerRed Hat OpenShift Data Science
Star Rating
(25)4.4 out of 5
Market Segments
Mid-Market (44.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Red Hat OpenShift Data ScienceSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon SageMaker excels in its AI Model Training Scalability with a score of 8.9, allowing for efficient handling of large datasets, while Red Hat OpenShift Data Science scores slightly lower at 8.6, which may impact users needing extensive model training capabilities.
- Reviewers mention that SageMaker's Data Ingestion & Wrangling feature, rated at 8.1, is less robust compared to Red Hat's 8.9, indicating that users may find it easier to prepare and manage data with OpenShift.
- G2 users highlight the Drag and Drop functionality in both platforms, but SageMaker scores 9.0, suggesting a more user-friendly interface for model development, while OpenShift's 8.7 may not be as intuitive for some users.
- Users on G2 appreciate SageMaker's AI High Availability features, which contribute to its high scalability score of 9.0, whereas OpenShift's 8.5 may not meet the needs of users requiring maximum uptime for their applications.
- Reviewers mention that SageMaker's Pre-Built Algorithms score of 8.4 provides a solid foundation for users looking to quickly implement machine learning solutions, while OpenShift's 8.7 indicates a slight edge in offering more diverse algorithm options.
- Users say that SageMaker's AI Cost per API Call is competitive at 9.2, making it a cost-effective choice for businesses, while OpenShift's 8.5 may lead to higher operational costs for users with extensive API usage.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableRed Hat OpenShift Data Science
No pricing availableFree Trial
Amazon SageMaker
No trial information availableRed Hat OpenShift Data Science
No trial information availableRatings
Meets Requirements
8.6
37
8.8
23
Ease of Use
8.4
38
8.5
23
Ease of Setup
8.5
25
Not enough data
Ease of Admin
8.4
20
Not enough data
Quality of Support
8.6
33
8.6
21
Has the product been a good partner in doing business?
9.2
20
Not enough data
Product Direction (% positive)
9.0
36
10.0
23
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
8.9
22
Model Development
8.7
29
8.8
23
8.2
28
8.8
23
8.3
33
8.7
23
8.9
33
8.6
23
Model Development
8.4
19
8.8
23
Machine/Deep Learning Services
8.9
26
8.5
22
9.1
28
8.3
20
8.9
25
8.6
20
9.0
28
8.3
20
Machine/Deep Learning Services
9.2
17
8.6
20
9.2
18
8.7
21
Deployment
8.6
32
8.6
22
8.6
32
8.8
22
9.0
31
8.5
22
Generative AI
8.6
6
8.3
5
9.2
6
8.7
5
8.3
5
8.7
5
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 Red Hat OpenShift Data Science are categorized as Data Science and Machine Learning Platforms
Unique Categories
Amazon SageMaker is categorized as MLOps Platforms, Generative AI Infrastructure, and Low-Code Machine Learning Platforms
Red Hat OpenShift Data Science has no unique categories
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Red Hat OpenShift Data Science
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%
Market Research
32.0%
Marketing and Advertising
20.0%
Information Technology and Services
8.0%
Computer Software
8.0%
Transportation/Trucking/Railroad
4.0%
Other
28.0%
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
Red Hat OpenShift Data Science has no discussions with answers
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