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Compare Amazon SageMaker and Nvidia AI Enterprise 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Small-Business (57.1% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Amazon SageMaker
Star Rating
(46)4.2 out of 5
Market Segments
Small-Business (33.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Amazon SageMakerNvidia AI Enterprise
Star Rating
(14)4.5 out of 5
Market Segments
Small-Business (57.1% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Nvidia AI EnterpriseSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon SageMaker excels in its comprehensive suite of built-in algorithms, making it easier for data scientists to deploy machine learning models quickly. In contrast, reviewers mention that Nvidia AI Enterprise shines with its GPU-accelerated capabilities, which significantly enhance performance for deep learning tasks.
- Reviewers mention that Amazon SageMaker has a slightly lower star rating (4.3) compared to Nvidia AI Enterprise (4.5), indicating a stronger overall satisfaction among users of Nvidia's product, particularly in high-performance computing environments.
- Users on G2 highlight that Amazon SageMaker is particularly favored by small businesses (33.3% of reviews), while Nvidia AI Enterprise has a larger share of small business users (53.8% of reviews), suggesting that Nvidia's offering may be more tailored to the needs of smaller organizations.
- Reviewers say that while both products have a high ease of setup score, Amazon SageMaker (8.5) is slightly behind Nvidia AI Enterprise (8.6), indicating that users find Nvidia's setup process marginally more straightforward.
- Users report that Amazon SageMaker has a strong quality of support (8.6), which is appreciated by many, while Nvidia AI Enterprise's support quality is rated slightly lower (8.3), suggesting that users may find more responsive assistance with SageMaker.
- G2 users mention that both products have an equal score for product direction (9.0), indicating that both Amazon SageMaker and Nvidia AI Enterprise are perceived positively in terms of their future development and feature enhancements.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableNvidia AI Enterprise
No pricing availableFree Trial
Amazon SageMaker
No trial information availableNvidia AI Enterprise
No trial information availableRatings
Meets Requirements
8.6
37
9.3
14
Ease of Use
8.4
38
9.0
14
Ease of Setup
8.5
25
8.7
14
Ease of Admin
8.4
20
Not enough data
Quality of Support
8.6
33
8.5
14
Has the product been a good partner in doing business?
9.2
20
Not enough data
Product Direction (% positive)
9.0
36
9.1
13
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
8.8
12
Not enough data
8.5
12
Not enough data
8.8
12
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.2
12
Not enough data
8.8
12
Not enough data
8.2
12
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.6
12
Not enough data
8.3
12
Not enough data
8.6
12
Security and Compliance - Generative AI Infrastructure
Not enough data
8.8
12
Not enough data
8.8
12
Not enough data
8.8
12
Usability and Support - Generative AI Infrastructure
Not enough data
8.8
12
Not enough data
8.9
12
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Security - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
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 Nvidia AI Enterprise are categorized as Generative AI Infrastructure
Unique Categories
Amazon SageMaker is categorized as MLOps Platforms, Data Science and Machine Learning Platforms, and Low-Code Machine Learning Platforms
Nvidia AI Enterprise is categorized as Large Language Model Operationalization (LLMOps)
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Nvidia AI Enterprise
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%
Information Technology and Services
35.7%
Computer Software
14.3%
Manufacturing
7.1%
Staffing and Recruiting
7.1%
Program Development
7.1%
Other
28.6%
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
Nvidia AI Enterprise has no discussions with answers
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