Compare Azure Machine Learning and SAS Viya 
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (34.1% 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
(733)4.3 out of 5
Market Segments
Enterprise (34.1% 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.
- G2 reviewers report that Azure Machine Learning excels in user experience, with many users appreciating its intuitive interface and predefined services that cater to business needs. One user noted the ease of creating experiments and deploying models as web services, highlighting its accessibility for normal users.
- Users say that SAS Viya stands out for its cloud-native architecture and scalability, which allows for seamless integration of data preparation, advanced analytics, and machine learning. Reviewers particularly like its user-friendly UI and the ability to access projects from various locations, making it a flexible choice for teams.
- According to verified reviews, Azure Machine Learning has a slight edge in ease of setup and administration, with users mentioning a straightforward onboarding process and manageable administrative tasks. This can be particularly beneficial for organizations looking to implement machine learning solutions quickly.
- Reviewers mention that SAS Viya provides robust analytical capabilities, especially in keyword and sentiment analysis. Users appreciate features like term maps and correlation displays, which enhance their ability to derive insights from data, making it a strong choice for businesses focused on data-driven decision-making.
- G2 reviewers highlight that while both platforms have similar star ratings, Azure Machine Learning's recent user feedback indicates a more favorable perception of its support quality. Users have noted the availability of resources and community support, which can be crucial for troubleshooting and implementation challenges.
- Users report that SAS Viya's market presence is bolstered by its extensive review count, suggesting a well-established reputation among small businesses. This can provide potential buyers with confidence in its reliability and effectiveness, especially for those in the small to mid-sized market segment.
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
534
Ease of Use
8.5
80
8.1
594
Ease of Setup
8.3
57
8.0
445
Ease of Admin
8.3
49
7.6
160
Quality of Support
8.6
74
8.3
505
Has the product been a good partner in doing business?
8.6
47
8.2
163
Product Direction (% positive)
9.0
80
8.9
532
Features by Category
Reports
Not enough data
8.3
243
Not enough data
8.1
234
Not enough data
8.5
237
Not enough data
8.1
234
Not enough data
8.4
231
Data Preparation
Not enough data
8.4
209
Not enough data
8.3
208
Data Modeling and Blending
Not enough data
8.4
209
Not enough data
8.7
208
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
7.8
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
231
Not enough data
8.3
232
Not enough data
8.4
232
Not enough data
8.1
228
Not enough data
8.1
230
Not enough data
8.2
226
Deployment & Integration - Analytics Platforms
Not enough data
8.3
89
Not enough data
8.2
89
Not enough data
8.1
88
Not enough data
8.5
89
Advanced Analytics
Not enough data
8.4
230
Not enough data
8.8
231
Not enough data
8.5
236
Performance & Scalability - Analytics Platforms
Not enough data
8.7
101
Not enough data
8.3
91
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
8.4
94
Not enough data
8.4
97
Not enough data
8.5
93
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
200
Not enough data
8.5
198
Not enough data
7.8
194
Not enough data
8.0
197
Data Source Access
Not enough data
8.5
114
Not enough data
8.3
116
Not enough data
8.1
112
Data Interaction
Not enough data
8.5
113
Not enough data
8.1
112
Not enough data
8.5
113
Not enough data
8.7
111
Not enough data
8.7
111
Not enough data
8.7
113
Not enough data
8.3
111
Not enough data
8.5
110
Data Exporting
Not enough data
8.4
112
Not enough data
8.3
112
Not enough data
8.5
109
Generative AI
Not enough data
Feature Not Available
Data
Not enough data
8.6
12
Not enough data
8.6
12
Not enough data
8.2
13
Not enough data
8.5
12
Analytics
Not enough data
7.9
12
Administration
Not enough data
8.3
23
Not enough data
8.6
23
Not enough data
8.3
23
Not enough data
8.6
24
Management
Not enough data
8.1
24
Not enough data
8.3
23
Not enough data
8.6
23
Not enough data
8.8
21
Not enough data
7.8
23
Compliance
Not enough data
8.3
22
Not enough data
Feature Not Available
Not enough data
8.3
23
Not enough data
8.5
23
Security
Not enough data
8.6
23
Not enough data
8.3
21
Not enough data
Feature Not Available
Data Quality
Not enough data
8.5
24
Not enough data
8.5
23
Not enough data
8.3
23
Maintainence
Not enough data
8.3
22
Not enough data
Feature Not Available
Generative AI
Not enough data
7.8
23
Not enough data
8.0
23
Agentic AI - Data Governance
Not enough data
8.7
5
Not enough data
9.3
5
Not enough data
9.3
5
Not enough data
9.3
5
Not enough data
8.7
5
Not enough data
9.3
5
Administration
Not enough data
8.9
135
Not enough data
8.9
139
Not enough data
8.8
136
Capabilities
Not enough data
9.2
141
Not enough data
8.9
138
Not enough data
8.7
136
Not enough data
8.6
133
Methodology
Not enough data
8.9
137
Not enough data
9.2
139
Not enough data
9.1
137
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Deployment
Not enough data
8.1
13
Not enough data
8.1
14
Not enough data
8.2
13
Not enough data
8.5
14
Not enough data
8.3
14
Deployment
Not enough data
8.2
14
Not enough data
8.3
13
Not enough data
8.3
13
Not enough data
8.2
14
Not enough data
8.7
13
Management
Not enough data
7.6
13
Not enough data
8.5
13
Not enough data
8.5
13
Not enough data
8.5
14
Operations
Not enough data
8.8
14
Not enough data
7.9
14
Not enough data
8.8
14
Management
Not enough data
7.9
13
Not enough data
8.2
14
Not enough data
8.1
13
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
System
8.6
22
8.4
73
Model Development
8.6
51
8.1
87
8.9
54
8.5
81
8.3
53
8.3
81
8.7
52
8.7
81
Model Development
8.4
21
8.3
70
Machine/Deep Learning Services
8.1
45
7.4
75
7.9
45
7.5
77
7.8
38
7.3
75
8.2
42
8.0
77
Machine/Deep Learning Services
8.7
21
7.6
69
8.5
21
7.9
71
Deployment
8.8
50
8.2
79
8.7
51
8.0
76
8.9
51
8.1
81
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
27
Not enough data
9.0
28
Not enough data
9.3
28
Not enough data
8.9
27
Not enough data
8.8
27
Maintenance
Not enough data
8.7
26
Not enough data
8.8
26
Not enough data
9.0
26
Security
Not enough data
8.9
28
Not enough data
8.6
27
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
15
Not enough data
8.7
15
Not enough data
9.0
15
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
9.0
15
Not enough data
8.8
15
Not enough data
8.7
15
Statistical Tool
Not enough data
8.6
73
Not enough data
8.6
74
Not enough data
8.6
74
Data Analysis
Not enough data
8.9
74
Not enough data
8.8
74
Decision Making
Not enough data
8.7
77
Not enough data
9.0
78
Not enough data
8.9
76
Not enough data
8.6
75
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Functionality
Not enough data
8.7
67
Not enough data
8.7
66
Not enough data
9.0
64
Not enough data
8.8
64
Not enough data
8.8
63
Management
Not enough data
9.2
66
Not enough data
9.0
62
Not enough data
8.9
64
Not enough data
8.9
62
Not enough data
Feature Not Available
Generative AI
Not enough data
8.3
60
Not enough data
8.2
61
Building Reports
Not enough data
8.5
200
Not enough data
8.5
198
Not enough data
7.8
194
Not enough data
8.0
197
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
12.4%
Computer Software
8.5%
Banking
8.3%
Higher Education
8.0%
Financial Services
6.2%
Other
56.6%
Discussions
What is Azure Machine Learning Studio used for?
2 Comments
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.
