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Compare IBM Watson Studio and SAS Viya 
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At a Glance
Market Segments
Enterprise (51.3% of reviews)
Small-Business (35.7% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
IBM Watson Studio
Star Rating
(164)4.2 out of 5
Market Segments
Enterprise (51.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Watson StudioSAS 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.
- G2 reviewers report that SAS Viya excels in overall user satisfaction, reflected in its higher G2 Score compared to IBM Watson Studio. Users appreciate its seamless integration with existing systems and the ability to run advanced analytics and AI within a unified platform, making it a strong choice for organizations looking for comprehensive data solutions.
- According to verified reviews, IBM Watson Studio is praised for its organization and support for a wide range of data science tasks. Users highlight its easy integration with existing datasets and the availability of AI models that can be deployed with minimal effort, making it a solid option for teams focused on low-code or no-code development.
- Users say that SAS Viya's cloud-native architecture and in-memory processing capabilities enable fast analytics on large datasets, which is particularly beneficial for businesses in regulated environments. This feature is often cited as a key advantage over IBM Watson Studio, which may not offer the same level of performance for large-scale data processing.
- Reviewers mention that while IBM Watson Studio provides a robust platform for data science, it sometimes struggles with specific workflow needs, leading to configuration challenges. This contrasts with SAS Viya, where users report a smoother initial setup and a more intuitive user experience.
- G2 reviewers highlight that SAS Viya's strong governance and security features are critical for organizations handling sensitive data. Users appreciate these aspects, especially in comparison to IBM Watson Studio, which, while secure, does not emphasize governance to the same extent.
- According to recent user feedback, both platforms offer valuable features, but SAS Viya's ability to automate workflows and integrate with SAS 9 is particularly noted as a significant advantage. Users find this integration enhances their analytical capabilities, while IBM Watson Studio is recognized for its educational resources, such as certifications and practice notebooks, which support user development.
Pricing
Entry-Level Pricing
IBM Watson Studio
No pricing availableSAS Viya
No pricing availableFree Trial
IBM Watson Studio
No trial information availableSAS Viya
Free Trial is available
Ratings
Meets Requirements
8.3
121
8.5
492
Ease of Use
8.0
122
8.1
549
Ease of Setup
7.6
100
8.0
411
Ease of Admin
7.8
95
7.5
144
Quality of Support
8.2
113
8.3
466
Has the product been a good partner in doing business?
8.0
94
8.2
147
Product Direction (% positive)
8.5
115
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
9.0
13
8.6
112
9.3
12
8.4
114
9.2
14
8.1
110
Data Interaction
9.0
14
8.5
111
9.2
12
8.2
110
9.4
12
8.5
111
9.1
13
8.7
109
9.2
12
8.7
109
9.2
13
8.7
110
9.1
13
8.3
109
9.6
12
8.5
108
Data Exporting
9.4
12
8.4
108
9.2
12
8.2
108
9.2
12
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
8.8
8
8.1
12
9.2
8
8.2
13
9.0
8
8.2
12
9.4
8
8.6
13
8.8
8
8.5
13
Deployment
9.0
8
8.2
13
8.8
8
8.3
12
8.8
8
8.5
12
9.4
8
8.3
13
9.2
8
8.8
12
Management
9.3
7
7.6
12
9.6
8
8.5
12
9.0
7
8.5
12
9.0
8
8.6
13
Operations
9.0
8
8.8
13
9.0
8
7.9
13
9.3
7
8.8
13
Management
9.5
7
7.9
12
9.4
8
8.3
13
8.8
7
8.2
12
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
System
9.0
12
8.4
67
Model Development
8.5
33
8.0
78
8.8
34
8.5
76
8.5
35
8.2
75
8.3
36
8.6
75
Model Development
9.4
13
8.4
66
Machine/Deep Learning Services
8.5
27
7.3
72
8.5
34
7.6
73
Feature Not Available
7.3
72
8.6
28
7.9
72
Machine/Deep Learning Services
8.9
12
7.5
66
9.0
12
7.9
66
Deployment
8.5
32
8.2
74
8.6
33
8.0
72
8.6
30
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
8.6
7
7.7
19
8.3
7
7.5
19
9.7
6
8.0
19
Data
8.6
7
8.3
20
8.6
7
8.6
19
Analysis
9.7
6
8.4
19
8.1
7
7.9
19
8.1
7
7.9
18
8.3
7
8.0
19
8.8
7
7.9
18
8.1
7
7.4
18
7.9
7
7.8
18
Customization
9.0
7
7.6
18
8.1
7
7.5
19
9.2
6
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
8.0
14
8.6
66
8.4
15
8.7
67
8.1
15
8.6
67
Data Analysis
8.7
15
8.9
66
9.0
14
8.8
66
Decision Making
8.6
14
8.7
67
8.6
15
9.0
68
8.3
13
8.8
67
8.7
14
8.6
67
Generative AI
9.3
5
Feature Not Available
8.3
5
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
IBM Watson Studio and SAS Viya are categorized as Text Analysis, Data Science and Machine Learning Platforms, Predictive Analytics, MLOps Platforms, and Data Preparation
Unique Categories
IBM Watson Studio has no unique categories
Reviews
Reviewers' Company Size
IBM Watson Studio
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
15.8%
Computer Software
13.3%
Telecommunications
8.2%
Banking
7.6%
Education Management
5.7%
Other
49.4%
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
IBM Watson Studio has no discussions with answers
SAS Viya has no discussions with answers
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