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Compare Microsoft Fabric and SAS Viya 
At a Glance
Market Segments
Enterprise (56.3% of reviews)
Enterprise (35.1% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Microsoft Fabric
Star Rating
(16)4.6 out of 5
Market Segments
Enterprise (56.3% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Microsoft FabricSAS Viya
Star Rating
(481)4.3 out of 5
Market Segments
Enterprise (35.1% of reviews)
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.
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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
16
8.5
381
Ease of Use
9.0
16
8.2
436
Ease of Setup
9.0
5
7.7
301
Ease of Admin
Not enough data
7.3
111
Quality of Support
9.1
16
8.3
362
Has the product been a good partner in doing business?
Not enough data
8.0
115
Product Direction (% positive)
10.0
16
8.8
385
Features by Category
Reports
Not enough data
8.2
138
Not enough data
7.8
132
Not enough data
8.3
135
Not enough data
7.9
132
Not enough data
8.2
128
Data Preparation
Not enough data
8.2
121
Not enough data
8.1
117
Data Modeling and Blending
Not enough data
8.4
123
Not enough data
8.6
120
Not enough data
8.4
122
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Agentic AI - Analytics Platforms
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
Self Service
Not enough data
8.1
131
Not enough data
8.1
131
Not enough data
8.2
130
Not enough data
8.1
129
Not enough data
8.1
126
Not enough data
8.1
128
Deployment & Integration - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics
Not enough data
8.4
129
Not enough data
8.7
128
Not enough data
8.3
126
Performance & Scalability - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI Capabilities - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Personalized Intelligence - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Building Reports
Not enough data
8.4
129
Not enough data
8.4
129
Not enough data
7.8
127
Not enough data
7.9
127
Data Source Access
Not enough data
8.6
80
Not enough data
8.4
80
Not enough data
8.2
79
Data Interaction
Not enough data
8.4
79
Not enough data
8.2
79
Not enough data
8.6
79
Not enough data
8.8
79
Not enough data
8.7
79
Not enough data
8.8
80
Not enough data
8.5
79
Not enough data
8.6
78
Data Exporting
Not enough data
8.3
78
Not enough data
8.1
78
Not enough data
8.5
78
Generative AI
Not enough data
Feature Not Available
Data
Not enough data
9.0
8
Not enough data
9.0
8
Not enough data
8.1
8
Not enough data
9.0
8
Analytics
Not enough data
7.9
8
Administration
Not enough data
8.0
19
Not enough data
8.3
19
Not enough data
8.0
19
Not enough data
8.4
20
Management
Not enough data
7.6
20
Not enough data
8.2
19
Not enough data
8.3
19
Not enough data
8.8
17
Not enough data
7.6
19
Compliance
Not enough data
8.1
18
Not enough data
Feature Not Available
Not enough data
8.1
19
Not enough data
8.2
19
Security
Not enough data
8.6
19
Not enough data
8.0
17
Not enough data
Feature Not Available
Data Quality
Not enough data
8.3
20
Not enough data
8.2
19
Not enough data
8.1
20
Maintainence
Not enough data
8.1
18
Not enough data
Feature Not Available
Generative AI
Not enough data
7.5
19
Not enough data
7.7
19
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
8.9
101
Not enough data
9.1
104
Not enough data
8.9
102
Capabilities
Not enough data
9.3
105
Not enough data
9.0
103
Not enough data
8.9
103
Not enough data
8.7
100
Methodology
Not enough data
9.0
102
Not enough data
9.2
103
Not enough data
9.3
102
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Deployment
8.9
14
8.5
8
8.7
14
8.1
9
8.7
14
7.7
8
8.8
14
8.9
9
9.0
14
8.1
9
Deployment
8.9
14
8.0
9
9.2
14
7.9
8
9.0
14
7.9
8
9.0
14
8.5
9
9.2
14
8.3
8
Management
8.6
13
7.5
8
8.7
14
7.9
8
8.8
13
8.1
8
8.8
13
8.1
9
Operations
8.8
14
8.3
9
8.8
14
7.6
9
8.9
14
8.5
9
Management
8.6
14
7.6
9
8.6
13
8.0
9
8.5
13
7.5
8
Generative AI
8.3
12
Feature Not Available
8.5
12
Feature Not Available
System
Not enough data
8.5
39
Not enough data
7.7
38
Not enough data
8.2
38
Model Development
Not enough data
8.1
44
Not enough data
8.6
44
Not enough data
8.2
43
Not enough data
8.6
43
Model Development
Not enough data
8.3
38
Not enough data
8.6
39
Not enough data
8.5
39
Machine/Deep Learning Services
Not enough data
7.1
43
Not enough data
7.6
43
Not enough data
7.2
43
Not enough data
8.0
43
Machine/Deep Learning Services
Not enough data
7.3
39
Not enough data
7.5
39
Not enough data
7.2
38
Not enough data
7.9
39
Deployment
Not enough data
8.1
43
Not enough data
7.8
42
Not enough data
7.8
40
Deployment
Not enough data
7.8
39
Not enough data
7.6
39
Not enough data
7.9
38
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
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
Financial Planning
Not enough data
7.5
6
Not enough data
8.1
6
Not enough data
8.6
6
Agentic AI - FP&A (Financial Planning & Analysis)
Not enough data
Not enough data
Not enough data
Not enough data
Financial Insight
Not enough data
7.0
5
Not enough data
8.3
5
Not enough data
7.2
6
Data
Not enough data
8.3
6
Not enough data
8.0
5
Not enough data
7.7
5
Not enough data
8.3
5
Status Communication
Not enough data
7.7
5
Not enough data
8.6
6
Not enough data
8.1
6
Not enough data
8.6
6
Management
Not enough data
8.2
17
Not enough data
8.6
18
Not enough data
9.2
18
Not enough data
8.8
17
Not enough data
8.9
17
Maintenance
Not enough data
8.8
16
Not enough data
9.1
16
Not enough data
9.1
16
Security
Not enough data
8.7
18
Not enough data
8.1
17
Integration
Not enough data
7.9
13
Not enough data
8.2
12
Business Logic
Not enough data
7.1
12
Not enough data
6.5
13
Not enough data
8.1
13
Management
Not enough data
7.5
12
Not enough data
7.4
13
Analytics
Not enough data
8.2
13
Not enough data
7.4
12
Deployment
Not enough data
7.9
12
Not enough data
7.4
12
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Agentic AI - Decision Management Platforms
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
Setup
Not enough data
7.9
14
Not enough data
7.4
14
Not enough data
8.1
14
Data
Not enough data
8.2
15
Not enough data
8.7
14
Analysis
Not enough data
8.6
14
Not enough data
8.3
14
Not enough data
8.1
13
Not enough data
8.3
14
Not enough data
8.1
13
Not enough data
7.8
13
Not enough data
8.2
13
Customization
Not enough data
7.9
13
Not enough data
7.7
14
Not enough data
8.1
14
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Integration - Machine Learning
Not enough data
7.6
17
Learning - Machine Learning
Not enough data
7.7
17
Not enough data
7.9
17
Not enough data
8.1
16
Agentic AI - Accounting & Finance
Not enough data
Not enough data
Statistical Tool
Not enough data
8.6
37
Not enough data
8.7
38
Not enough data
8.7
38
Data Analysis
Not enough data
9.1
37
Not enough data
8.8
37
Decision Making
Not enough data
8.7
39
Not enough data
9.0
40
Not enough data
8.6
40
Not enough data
8.7
40
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Functionality
Not enough data
8.9
45
Not enough data
8.8
45
Not enough data
9.1
44
Not enough data
8.8
44
Not enough data
9.0
44
Management
Not enough data
9.3
45
Not enough data
9.2
42
Not enough data
8.9
44
Not enough data
9.0
42
Not enough data
Feature Not Available
Generative AI
Not enough data
8.5
39
Not enough data
8.6
40
Building Reports
Not enough data
8.4
129
Not enough data
8.4
129
Not enough data
7.8
127
Not enough data
7.9
127
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, and Decision Management 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
Education Management
18.8%
Manufacturing
12.5%
Information Technology and Services
12.5%
Electrical/Electronic Manufacturing
12.5%
Consulting
6.3%
Other
37.5%
Pharmaceuticals
13.7%
Higher Education
8.7%
Banking
8.0%
Financial Services
6.5%
Information Technology and Services
5.6%
Other
57.5%
Most Helpful Reviews
Microsoft Fabric
Most Helpful Favorable Review
Verified User in Logistics and Supply Chain
I like Microsoft Fabric because it's a unified platform that combines services like data lakes, data engineering and business intelligence tools. Also, it is easy to use and has really good integration with other Microsoft services.
Most Helpful Critical Review
Muhammed M.
Verified User in Information Technology and Services
It is sometimes difficult to use with non microsoft technologies. It is complex to understand for the new users. Cloud have access issues sometimes.
SAS Viya
Most Helpful Favorable Review
Daniel W.
Verified User in Pharmaceuticals
1. Rapid analysis of vast volumes of data is possible thanks to SAS Viya's high-performance analytics. 2. Scalability: SAS Viya is built to handle large-scale analytics projects and gives users the flexibility to scale their analytics requirements up or...
Most Helpful Critical Review
Verified User in Retail
I think the SAS suite in general is too pricey when open source options allow more flexibility
Verified User in Logistics and Supply Chain
I like Microsoft Fabric because it's a unified platform that combines services like data lakes, data engineering and business intelligence tools. Also, it is easy to use and has really good integration with other Microsoft services.
Daniel W.
Verified User in Pharmaceuticals
1. Rapid analysis of vast volumes of data is possible thanks to SAS Viya's high-performance analytics. 2. Scalability: SAS Viya is built to handle large-scale analytics projects and gives users the flexibility to scale their analytics requirements up or...
Muhammed M.
Verified User in Information Technology and Services
It is sometimes difficult to use with non microsoft technologies. It is complex to understand for the new users. Cloud have access issues sometimes.
Verified User in Retail
I think the SAS suite in general is too pricey when open source options allow more flexibility
Alternatives
Discussions
Microsoft Fabric has no discussions with answers
SAS Viya has no discussions with answers
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