Introducing G2.ai, the future of software buying.Try now
Compare Azure Machine Learning and SAS Viya 
Featured Products
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Kpow for Apache Kafka®
Visit Website
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Aleph
Visit Website
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
RaimaDB
Visit Website
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Small-Business (35.7% 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)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Azure Machine LearningSAS Viya
Star Rating
(615)4.3 out of 5
Market Segments
Small-Business (35.7% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about SAS ViyaSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Azure Machine Learning excels in real-time processing with a score of 8.8, making it a preferred choice for applications requiring immediate data insights. In contrast, SAS Viya, while competent, scores slightly lower in this area, indicating it may not be as responsive in time-sensitive scenarios.
- Reviewers mention that Azure Machine Learning offers superior data visualization capabilities, scoring 8.5 compared to SAS Viya's 8.3. This difference highlights Azure's ability to create more engaging and informative visual representations of data, which is crucial for effective decision-making.
- G2 users highlight Azure Machine Learning's ease of setup with a score of 8.4, suggesting a more user-friendly onboarding experience. SAS Viya, with a score of 7.9, may present a steeper learning curve for new users, potentially impacting initial productivity.
- Users on G2 report that Azure Machine Learning's quality of support is rated at 8.6, indicating a strong customer service experience. SAS Viya, while still good at 8.3, may not provide the same level of responsiveness and assistance, which can be critical for users needing timely help.
- Reviewers mention that Azure Machine Learning shines in language flexibility with a score of 9.0, allowing users to work in various programming languages seamlessly. SAS Viya, scoring 8.3, may not offer the same breadth of language support, which could limit flexibility for developers.
- Users say that Azure Machine Learning's collaboration features are rated highly at 8.9, facilitating teamwork and project management effectively. In comparison, SAS Viya's collaboration score of 7.5 suggests it may lack some of the integrated tools that enhance team productivity.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableSAS Viya
No pricing availableFree Trial
Azure Machine Learning
No trial information availableSAS Viya
Free Trial is available
Ratings
Meets Requirements
8.5
81
8.5
492
Ease of Use
8.5
80
8.1
549
Ease of Setup
8.3
57
8.0
411
Ease of Admin
8.3
49
7.5
144
Quality of Support
8.6
74
8.3
466
Has the product been a good partner in doing business?
8.6
47
8.2
147
Product Direction (% positive)
9.0
80
8.9
491
Features by Category
Reports
Not enough data
8.3
237
Not enough data
8.0
232
Not enough data
8.5
234
Not enough data
8.1
232
Not enough data
8.4
228
Data Preparation
Not enough data
8.4
209
Not enough data
8.3
205
Data Modeling and Blending
Not enough data
8.4
209
Not enough data
8.7
207
Not enough data
8.5
209
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Agentic AI - Analytics Platforms
Not enough data
7.9
92
Not enough data
7.9
90
Not enough data
8.0
90
Not enough data
8.0
89
Not enough data
7.9
89
Not enough data
7.6
89
Not enough data
8.1
89
Self Service
Not enough data
8.3
230
Not enough data
8.3
230
Not enough data
8.4
229
Not enough data
8.2
228
Not enough data
8.1
226
Not enough data
8.2
226
Deployment & Integration - Analytics Platforms
Not enough data
8.3
88
Not enough data
8.2
89
Not enough data
8.1
88
Not enough data
8.5
88
Advanced Analytics
Not enough data
8.4
228
Not enough data
8.7
226
Not enough data
8.5
225
Performance & Scalability - Analytics Platforms
Not enough data
8.5
89
Not enough data
8.4
89
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
8.4
91
Not enough data
8.3
89
Not enough data
8.4
90
Agentic AI Capabilities - Analytics Platforms
Not enough data
7.8
88
Not enough data
7.9
87
Not enough data
8.0
87
Not enough data
7.8
88
Personalized Intelligence - Analytics Platforms
Not enough data
8.1
88
Not enough data
8.0
87
Not enough data
7.9
88
Building Reports
Not enough data
8.5
198
Not enough data
8.5
197
Not enough data
7.8
192
Not enough data
7.9
193
Data Source Access
Not enough data
8.6
112
Not enough data
8.4
114
Not enough data
8.1
110
Data Interaction
Not enough data
8.5
111
Not enough data
8.2
110
Not enough data
8.5
111
Not enough data
8.7
109
Not enough data
8.7
109
Not enough data
8.7
110
Not enough data
8.3
109
Not enough data
8.5
108
Data Exporting
Not enough data
8.4
108
Not enough data
8.2
108
Not enough data
8.5
107
Generative AI
Not enough data
Feature Not Available
Data
Not enough data
8.6
12
Not enough data
8.6
12
Not enough data
8.1
12
Not enough data
8.5
12
Analytics
Not enough data
7.9
12
Administration
Not enough data
8.4
22
Not enough data
8.6
22
Not enough data
8.3
22
Not enough data
8.7
23
Management
Not enough data
8.0
23
Not enough data
8.3
22
Not enough data
8.6
22
Not enough data
8.9
20
Not enough data
7.8
22
Compliance
Not enough data
8.3
21
Not enough data
Feature Not Available
Not enough data
8.3
22
Not enough data
8.5
22
Security
Not enough data
8.6
22
Not enough data
8.3
20
Not enough data
Feature Not Available
Data Quality
Not enough data
8.6
23
Not enough data
8.5
22
Not enough data
8.3
22
Maintainence
Not enough data
8.3
21
Not enough data
Feature Not Available
Generative AI
Not enough data
7.8
22
Not enough data
8.0
22
Agentic AI - Data Governance
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
Administration
Not enough data
8.8
134
Not enough data
8.9
137
Not enough data
8.8
134
Capabilities
Not enough data
9.2
138
Not enough data
8.9
136
Not enough data
8.7
135
Not enough data
8.6
132
Methodology
Not enough data
8.9
135
Not enough data
9.2
137
Not enough data
9.1
136
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Deployment
Not enough data
8.1
12
Not enough data
8.2
13
Not enough data
8.2
12
Not enough data
8.6
13
Not enough data
8.5
13
Deployment
Not enough data
8.2
13
Not enough data
8.3
12
Not enough data
8.5
12
Not enough data
8.3
13
Not enough data
8.8
12
Management
Not enough data
7.6
12
Not enough data
8.5
12
Not enough data
8.5
12
Not enough data
8.6
13
Operations
Not enough data
8.8
13
Not enough data
7.9
13
Not enough data
8.8
13
Management
Not enough data
7.9
12
Not enough data
8.3
13
Not enough data
8.2
12
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
System
8.6
22
8.4
67
Model Development
8.6
51
8.0
78
8.9
54
8.5
76
8.3
53
8.2
75
8.7
52
8.6
75
Model Development
8.4
21
8.4
66
Machine/Deep Learning Services
8.1
45
7.3
72
7.9
45
7.6
73
7.8
38
7.3
72
8.2
42
7.9
72
Machine/Deep Learning Services
8.7
21
7.5
66
8.5
21
7.9
66
Deployment
8.8
50
8.2
74
8.7
51
8.0
72
8.9
51
8.0
72
Generative AI
8.5
10
Feature Not Available
8.2
10
Feature Not Available
7.5
10
Feature Not Available
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
7.6
26
Not enough data
7.2
26
Not enough data
7.4
26
Not enough data
7.1
26
Not enough data
7.0
26
Not enough data
7.0
26
Not enough data
7.4
26
Financial Planning
Not enough data
7.8
10
Not enough data
8.2
10
Not enough data
8.5
10
Agentic AI - FP&A (Financial Planning & Analysis)
Not enough data
Not enough data
Not enough data
Not enough data
Financial Insight
Not enough data
8.0
10
Not enough data
8.8
10
Not enough data
7.9
11
Data
Not enough data
8.6
11
Not enough data
8.5
10
Not enough data
8.2
10
Not enough data
8.5
10
Status Communication
Not enough data
7.8
10
Not enough data
8.3
11
Not enough data
8.2
11
Not enough data
8.5
11
Management
Not enough data
8.8
26
Not enough data
9.0
27
Not enough data
9.4
27
Not enough data
9.0
26
Not enough data
8.9
26
Maintenance
Not enough data
8.8
25
Not enough data
8.9
25
Not enough data
9.1
25
Security
Not enough data
9.0
27
Not enough data
8.6
26
Integration
Not enough data
8.0
20
Not enough data
8.2
19
Business Logic
Not enough data
7.5
19
Not enough data
7.3
19
Not enough data
8.2
19
Management
Not enough data
7.7
18
Not enough data
7.5
19
Analytics
Not enough data
8.4
20
Not enough data
7.6
19
Deployment
Not enough data
8.2
19
Not enough data
7.6
17
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Agentic AI - Decision Management Platforms
Not enough data
7.5
6
Not enough data
6.7
6
Not enough data
6.4
6
Not enough data
6.7
6
Not enough data
6.1
6
Not enough data
6.7
6
Not enough data
7.5
6
Setup
Not enough data
7.7
19
Not enough data
7.5
19
Not enough data
8.0
19
Data
Not enough data
8.3
20
Not enough data
8.6
19
Analysis
Not enough data
8.4
19
Not enough data
7.9
19
Not enough data
7.9
18
Not enough data
8.0
19
Not enough data
7.9
18
Not enough data
7.4
18
Not enough data
7.8
18
Customization
Not enough data
7.6
18
Not enough data
7.5
19
Not enough data
8.1
19
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
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
Integration - Machine Learning
Not enough data
8.2
34
Learning - Machine Learning
Not enough data
8.4
36
Not enough data
8.4
36
Not enough data
8.5
35
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
Agentic AI - Accounting & Finance
Not enough data
Not enough data
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
8.7
14
Not enough data
8.8
14
Not enough data
9.0
14
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
9.0
14
Not enough data
8.9
14
Not enough data
8.7
14
Statistical Tool
Not enough data
8.6
66
Not enough data
8.7
67
Not enough data
8.6
67
Data Analysis
Not enough data
8.9
66
Not enough data
8.8
66
Decision Making
Not enough data
8.7
67
Not enough data
9.0
68
Not enough data
8.8
67
Not enough data
8.6
67
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Functionality
Not enough data
8.7
64
Not enough data
8.7
64
Not enough data
9.0
62
Not enough data
8.8
63
Not enough data
8.8
62
Management
Not enough data
9.2
64
Not enough data
9.0
61
Not enough data
8.9
63
Not enough data
8.9
61
Not enough data
Feature Not Available
Generative AI
Not enough data
8.2
59
Not enough data
8.2
60
Building Reports
Not enough data
8.5
198
Not enough data
8.5
197
Not enough data
7.8
192
Not enough data
7.9
193
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 SAS Viya are categorized as MLOps Platforms, Data Science and Machine Learning Platforms, and Low-Code Machine Learning Platforms
Unique Categories
Azure Machine Learning is categorized as Large Language Model Operationalization (LLMOps) and Generative AI Infrastructure
SAS Viya is categorized as Statistical Analysis, Data Governance, Event Stream Processing, Data Preparation, Text Analysis, Machine Learning, Analytics Platforms, Predictive Analytics, Database Management Systems (DBMS), FP&A (Financial Planning & Analysis), Data Quality, and Decision Management Platforms
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
SAS Viya
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%
Pharmaceuticals
13.8%
Higher Education
9.1%
Banking
8.4%
Financial Services
6.6%
Information Technology and Services
6.3%
Other
55.8%
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
SAS Viya has no discussions with answers
Hunting for software insights?
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.
