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Compare Azure Machine Learning and MATLAB 
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At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (42.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Azure Machine Learning
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (38.8% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Azure Machine LearningMATLAB
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, Azure Machine Learning lacks dedicated 3D modeling features, which may limit its appeal for users focused on complex simulations.
- Reviewers mention that Azure Machine Learning offers superior scalability with a score of 9.2, particularly in its managed service deployment, which is crucial for enterprises looking to handle large datasets and high-volume workloads. MATLAB, while robust, scores lower at 8.4 in scalability, which may affect performance in large-scale applications.
- G2 users highlight the ease of use of Azure Machine Learning, scoring 8.6, which is slightly higher than MATLAB's 8.3. This suggests that Azure's interface and user experience may be more intuitive for new users, making it easier to adopt for teams without extensive technical backgrounds.
- Reviewers say that MATLAB's pre-built algorithms receive high praise with a score of 8.9, providing users with a rich library for various applications. In comparison, Azure Machine Learning's pre-built algorithms score lower at 8.3, which may require users to invest more time in developing custom solutions.
- Users on G2 report that Azure Machine Learning's data ingestion and wrangling capabilities are rated at 8.7, indicating a strong performance in handling and preparing data for analysis. MATLAB's score of 8.5 is commendable but suggests that Azure may offer a more streamlined experience for data preparation tasks.
- Reviewers mention that both platforms provide quality support, each scoring 8.6, but users report that Azure Machine Learning's community activity and documentation quality are particularly beneficial for troubleshooting and learning, giving it an edge in user support resources.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableMATLAB
No pricing availableFree Trial
Azure Machine Learning
No trial information availableMATLAB
No trial information availableRatings
Meets Requirements
8.5
81
9.0
666
Ease of Use
8.5
80
8.3
675
Ease of Setup
8.3
57
8.6
77
Ease of Admin
8.3
49
8.4
41
Quality of Support
8.6
74
8.6
619
Has the product been a good partner in doing business?
8.6
47
8.4
38
Product Direction (% positive)
9.0
80
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
8.6
22
8.5
74
Model Development
8.6
51
8.5
96
8.9
54
8.6
94
8.3
53
9.0
102
8.7
52
8.6
98
Model Development
8.4
21
8.7
79
Machine/Deep Learning Services
8.1
45
8.8
88
7.9
45
8.3
78
7.8
38
8.2
76
8.2
42
8.6
90
Machine/Deep Learning Services
8.7
21
8.5
69
8.5
21
8.7
77
Deployment
8.8
50
8.4
82
8.7
51
8.7
92
8.9
51
8.4
93
Generative AI
8.5
10
8.0
14
8.2
10
8.3
14
7.5
10
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
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
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
Azure Machine Learning and MATLAB are categorized as Data Science and Machine Learning Platforms
Unique Categories
Azure Machine Learning is categorized as MLOps Platforms, Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, and Low-Code Machine Learning Platforms
MATLAB is categorized as Big Data Analytics and Simulation & CAE
Reviews
Reviewers' Company Size
Azure Machine Learning
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
28.2%
Computer Software
14.1%
Management Consulting
8.2%
Education Management
5.9%
Higher Education
4.7%
Other
38.8%
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 Azure Machine Learning Studio used for?
1 Comment
AR
In short, to build, deploy, and manage high-quality models faster and with confidence.Read more
Azure Machine Learning 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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