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Compare Amazon SageMaker and MATLAB 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Enterprise (42.0% 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 SageMakerMATLAB
Star Rating
(759)4.5 out of 5
Market Segments
Enterprise (42.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about MATLABSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that MATLAB excels in its 3D/solid modeling tools, with a rating of 8.4, making it a preferred choice for engineers and scientists who require advanced modeling capabilities. In contrast, Amazon SageMaker, while strong in machine learning, does not focus on these specific modeling tools.
- Reviewers mention that MATLAB's data ingestion and wrangling capabilities are rated at 8.5, which is beneficial for users needing to preprocess data efficiently. However, Amazon SageMaker's rating of 8.1 in this area indicates it may not be as robust for users focused on data preparation.
- G2 users highlight that Amazon SageMaker shines in its AI model training scalability, scoring 9.0, which is crucial for businesses looking to scale their machine learning operations. MATLAB, while competent, does not match this level of scalability in AI training.
- Users on G2 appreciate MATLAB's ease of setup, rated at 8.6, which allows for a smoother onboarding experience. In comparison, Amazon SageMaker's ease of setup is rated slightly lower at 8.4, suggesting that users may face a bit more complexity when starting out.
- Reviewers mention that Amazon SageMaker offers superior drag-and-drop functionality, scoring 9.0, which enhances user experience for those who prefer visual programming. MATLAB's drag-and-drop feature, rated at 8.7, is effective but does not provide the same level of user-friendliness.
- Users say that MATLAB's quality of support is rated at 8.6, which is commendable, but Amazon SageMaker slightly edges it out with a score of 8.7, indicating a more responsive support system for users needing assistance.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableMATLAB
No pricing availableFree Trial
Amazon SageMaker
No trial information availableMATLAB
No trial information availableRatings
Meets Requirements
8.6
37
9.0
666
Ease of Use
8.4
38
8.3
675
Ease of Setup
8.5
25
8.6
77
Ease of Admin
8.4
20
8.4
41
Quality of Support
8.6
33
8.6
619
Has the product been a good partner in doing business?
9.2
20
8.4
38
Product Direction (% positive)
9.0
36
8.8
664
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
Design
Not enough data
8.4
147
Not enough data
8.2
164
Not enough data
8.1
166
Not enough data
8.0
141
Tools
Not enough data
8.4
127
Not enough data
8.5
150
Not enough data
8.4
132
Work
Not enough data
8.8
159
Not enough data
8.9
161
Not enough data
8.7
145
Not enough data
8.3
135
Not enough data
8.4
141
Environment
Not enough data
8.4
163
Not enough data
8.7
162
Not enough data
8.4
138
Not enough data
8.8
177
System
8.2
19
8.5
74
Model Development
8.7
29
8.5
96
8.2
28
8.6
94
8.3
33
9.0
102
8.9
33
8.6
98
Model Development
8.4
19
8.7
79
Machine/Deep Learning Services
8.9
26
8.8
88
9.1
28
8.3
78
8.9
25
8.2
76
9.0
28
8.6
90
Machine/Deep Learning Services
9.2
17
8.5
69
9.2
18
8.7
77
Deployment
8.6
32
8.4
82
8.6
32
8.7
92
9.0
31
8.4
93
Generative AI
8.6
6
8.0
14
9.2
6
8.3
14
8.3
5
7.5
14
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.7
10
Not enough data
8.7
10
Not enough data
7.8
10
Not enough data
9.0
10
Not enough data
7.8
10
Not enough data
7.7
10
Not enough data
8.0
10
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
Data Transformation
Not enough data
8.7
73
|
Verified
Not enough data
8.6
45
|
Verified
Connectivity
Not enough data
8.3
47
|
Verified
Not enough data
8.6
50
|
Verified
Not enough data
8.4
60
|
Verified
Not enough data
8.3
52
|
Verified
Operations
Not enough data
9.1
73
|
Verified
Not enough data
8.9
68
|
Verified
Not enough data
Feature Not Available
Not enough data
8.8
60
|
Verified
Not enough data
8.8
36
|
Verified
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
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
Categories
Categories
Shared Categories
Amazon SageMaker and MATLAB 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
MATLAB is categorized as Big Data Analytics and Simulation & CAE
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
MATLAB
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%
Higher Education
15.6%
Research
12.9%
Computer Software
6.9%
Mechanical or Industrial Engineering
6.8%
Education Management
6.2%
Other
51.6%
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
Any good website to discuss about the matlab programming?
3 Comments
TD
Mathworks site would be better place since it's the official website of the producers of the matlabRead more
Can I use Matlab for free?
3 Comments
PC
You can use the trial version of MATLAB for free. Also, if you pursue any online courses e.g. from coursera, they allow you to use MATLAB for free for the...Read more
Is it possible to check the output of Simulink terminal if I am not keeping a scope?
2 Comments
MA
Yes, If you prepared from the beginning "to work space" block for all the Simulink model. You can view any variable you want. Read more
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