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Compare Microsoft Fabric and SAS Viya 
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At a Glance
Market Segments
Enterprise (55.6% of reviews)
Small-Business (35.7% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Microsoft Fabric
Star Rating
(18)4.6 out of 5
Market Segments
Enterprise (55.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Microsoft FabricSAS Viya
Star Rating
(618)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 SAS Viya excels in data processing capabilities, with a score of 8.8, while Microsoft Fabric follows closely with a score of 8.6. Reviewers mention that SAS Viya's robust data processing features allow for efficient handling of large datasets, making it a preferred choice for enterprises focused on data-heavy operations.
- Reviewers mention that Microsoft Fabric shines in ease of use, scoring 8.9 compared to SAS Viya's 8.2. Users on G2 appreciate the intuitive interface of Microsoft Fabric, which simplifies the onboarding process for new users, making it more accessible for teams without extensive technical expertise.
- G2 users highlight the superior quality of support provided by Microsoft Fabric, with a score of 9.0, while SAS Viya scores 8.3. Users report that Microsoft Fabric's support team is responsive and helpful, which is crucial for organizations that rely on timely assistance for their analytics needs.
- Users say that SAS Viya offers a broader range of data source access, scoring 8.6, compared to Microsoft Fabric's 8.3. Reviewers mention that this flexibility in data connectivity is essential for enterprises that need to integrate various data sources seamlessly into their analytics workflows.
- Reviewers mention that Microsoft Fabric excels in scalability, achieving a score of 9.0, while SAS Viya scores 7.9. Users report that Microsoft Fabric's architecture allows for easy scaling as business needs grow, making it a better option for organizations anticipating rapid growth or increased data demands.
- Users on G2 highlight that SAS Viya's reporting capabilities, particularly in custom reporting and dashboards, score 8.3 and 8.1 respectively, which are slightly lower than Microsoft Fabric's scores. Reviewers say that while both products offer strong reporting features, SAS Viya's flexibility in custom reporting is particularly beneficial for users needing tailored analytics solutions.
Pricing
Entry-Level Pricing
Microsoft Fabric
No pricing availableSAS Viya
No pricing availableFree Trial
Microsoft Fabric
No trial information availableSAS Viya
Free Trial is available
Ratings
Meets Requirements
9.3
18
8.5
492
Ease of Use
9.0
18
8.1
549
Ease of Setup
9.0
7
8.0
411
Ease of Admin
Not enough data
7.5
144
Quality of Support
9.1
18
8.3
466
Has the product been a good partner in doing business?
Not enough data
8.2
147
Product Direction (% positive)
10.0
18
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
8.9
16
8.1
12
8.9
16
8.2
13
8.8
16
8.2
12
8.9
16
8.6
13
9.2
16
8.5
13
Deployment
9.0
16
8.2
13
9.3
16
8.3
12
9.2
16
8.5
12
9.2
16
8.3
13
9.3
16
8.8
12
Management
8.8
15
7.6
12
8.9
16
8.5
12
9.0
15
8.5
12
9.0
15
8.6
13
Operations
9.0
16
8.8
13
9.0
16
7.9
13
9.1
16
8.8
13
Management
8.6
16
7.9
12
8.7
15
8.3
13
8.7
15
8.2
12
Generative AI
8.1
14
Feature Not Available
8.2
14
Feature Not Available
System
Not enough data
8.4
67
Model Development
Not enough data
8.0
78
Not enough data
8.5
76
Not enough data
8.2
75
Not enough data
8.6
75
Model Development
Not enough data
8.4
66
Machine/Deep Learning Services
Not enough data
7.3
72
Not enough data
7.6
73
Not enough data
7.3
72
Not enough data
7.9
72
Machine/Deep Learning Services
Not enough data
7.5
66
Not enough data
7.9
66
Deployment
Not enough data
8.2
74
Not enough data
8.0
72
Not enough data
8.0
72
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
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
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
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
Microsoft Fabric and SAS Viya are categorized as MLOps Platforms
Unique Categories
Microsoft Fabric has no unique categories
SAS Viya is categorized as Statistical Analysis, Data Governance, Event Stream Processing, Data Preparation, Text Analysis, Data Science and Machine Learning Platforms, Machine Learning, Analytics Platforms, Predictive Analytics, Database Management Systems (DBMS), FP&A (Financial Planning & Analysis), Data Quality, Decision Management Platforms, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Microsoft Fabric
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
16.7%
Education Management
16.7%
Manufacturing
11.1%
Electrical/Electronic Manufacturing
11.1%
Consulting
5.6%
Other
38.9%
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
Microsoft Fabric has no discussions with answers
SAS Viya has no discussions with answers
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