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Compare SAS Viya and Vertex AI 
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At a Glance
Market Segments
Small-Business (35.7% of reviews)
Small-Business (41.1% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
SAS 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 ViyaVertex AI
Star Rating
(591)4.3 out of 5
Market Segments
Small-Business (41.1% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Vertex AI excels in user experience, with many praising its intuitive design that simplifies the machine learning process. Users highlight how it allows them to transition effortlessly from experimenting in notebooks to deploying production pipelines without the hassle of juggling multiple tools.
- Users say that SAS Viya offers strong integration capabilities, particularly with SAS 9, which enhances its functionality for users familiar with the SAS ecosystem. Reviewers appreciate its ability to streamline data for analysis and automate workflows within a unified platform.
- According to verified reviews, Vertex AI stands out for its high satisfaction ratings, reflected in its impressive G2 Scores across various categories. Users frequently mention the accuracy and authenticity of the AI's responses, which significantly aids in their decision-making processes.
- Reviewers mention that while SAS Viya provides robust governance and security features, which are crucial for regulated environments, some users find its initial setup to be more complex compared to Vertex AI's straightforward onboarding experience.
- Users highlight that Vertex AI's ease of use is a major advantage, with many stating that it makes navigating AI development tasks feel effortless. This is particularly beneficial for small businesses looking to leverage machine learning without extensive technical expertise.
- G2 reviewers note that SAS Viya's cloud-native architecture enables fast analytics on large datasets, but some users feel that it may not be as user-friendly as Vertex AI, especially for those new to machine learning, which could hinder adoption in smaller teams.
Pricing
Entry-Level Pricing
SAS Viya
No pricing availableVertex AI
Try Vertex AI Free
Pay As You Go
Per Month
New customers get $300 in free credits to spend on Vertex AI.
- A unified UI for the entire ML workflow
- Pre-trained APIs for vision, video, natural language, and more
- End-to-end integration for data and AI
Free Trial
SAS Viya
Free Trial is available
Vertex AI
Free Trial is available
Ratings
Meets Requirements
8.5
492
8.6
358
Ease of Use
8.1
549
8.2
367
Ease of Setup
8.0
411
8.1
290
Ease of Admin
7.5
144
7.9
141
Quality of Support
8.3
466
8.1
334
Has the product been a good partner in doing business?
8.2
147
8.2
135
Product Direction (% positive)
8.9
491
9.2
352
Features by Category
Reports
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
Not enough data
Data Preparation
8.4
209
Not enough data
8.3
205
Not enough data
Data Modeling and Blending
8.4
209
Not enough data
8.7
207
Not enough data
8.5
209
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Agentic AI - Analytics Platforms
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
Not enough data
Self Service
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
Not enough data
Deployment & Integration - Analytics Platforms
8.3
88
Not enough data
8.2
89
Not enough data
8.1
88
Not enough data
8.5
88
Not enough data
Advanced Analytics
8.4
228
Not enough data
8.7
226
Not enough data
8.5
225
Not enough data
Performance & Scalability - Analytics Platforms
8.5
89
Not enough data
8.4
89
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
8.4
91
Not enough data
8.3
89
Not enough data
8.4
90
Not enough data
Agentic AI Capabilities - Analytics Platforms
7.8
88
Not enough data
7.9
87
Not enough data
8.0
87
Not enough data
7.8
88
Not enough data
Personalized Intelligence - Analytics Platforms
8.1
88
Not enough data
8.0
87
Not enough data
7.9
88
Not enough data
Building Reports
8.5
198
Not enough data
8.5
197
Not enough data
7.8
192
Not enough data
7.9
193
Not enough data
Data Source Access
8.6
112
Not enough data
8.4
114
Not enough data
8.1
110
Not enough data
Data Interaction
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
Not enough data
Data Exporting
8.4
108
Not enough data
8.2
108
Not enough data
8.5
107
Not enough data
Generative AI
Feature Not Available
Not enough data
Data
8.6
12
Not enough data
8.6
12
Not enough data
8.1
12
Not enough data
8.5
12
Not enough data
Analytics
7.9
12
Not enough data
Administration
8.4
22
Not enough data
8.6
22
Not enough data
8.3
22
Not enough data
8.7
23
Not enough data
Management
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
Not enough data
Compliance
8.3
21
Not enough data
Feature Not Available
Not enough data
8.3
22
Not enough data
8.5
22
Not enough data
Security
8.6
22
Not enough data
8.3
20
Not enough data
Feature Not Available
Not enough data
Data Quality
8.6
23
Not enough data
8.5
22
Not enough data
8.3
22
Not enough data
Maintainence
8.3
21
Not enough data
Feature Not Available
Not enough data
Generative AI
7.8
22
Not enough data
8.0
22
Not enough data
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
8.8
134
Not enough data
8.9
137
Not enough data
8.8
134
Not enough data
Capabilities
9.2
138
Not enough data
8.9
136
Not enough data
8.7
135
Not enough data
8.6
132
Not enough data
Methodology
8.9
135
Not enough data
9.2
137
Not enough data
9.1
136
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Deployment
8.1
12
8.3
73
8.2
13
8.1
74
8.2
12
8.3
74
8.6
13
8.3
70
8.5
13
8.8
70
Deployment
8.2
13
8.4
73
8.3
12
8.3
72
8.5
12
8.4
71
8.3
13
8.5
71
8.8
12
8.7
69
Management
7.6
12
8.3
70
8.5
12
8.5
69
8.5
12
8.0
69
8.6
13
8.1
69
Operations
8.8
13
8.2
69
7.9
13
8.4
70
8.8
13
8.3
70
Management
7.9
12
8.1
68
8.3
13
8.4
69
8.2
12
8.3
68
Generative AI
Feature Not Available
8.2
34
Feature Not Available
8.4
34
System
8.4
67
8.2
170
Model Development
8.0
78
8.4
202
8.5
76
7.9
179
8.2
75
8.4
200
8.6
75
8.5
202
Model Development
8.4
66
8.2
165
Machine/Deep Learning Services
7.3
72
8.2
200
7.6
73
8.4
196
7.3
72
8.2
195
7.9
72
8.2
178
Machine/Deep Learning Services
7.5
66
8.5
165
7.9
66
8.4
163
Deployment
8.2
74
8.2
193
8.0
72
8.3
194
8.0
72
8.5
193
Generative AI
Feature Not Available
8.3
102
Feature Not Available
8.2
102
Feature Not Available
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
7.6
26
8.1
34
7.2
26
7.8
34
7.4
26
7.7
34
7.1
26
7.8
34
7.0
26
8.4
34
7.0
26
7.8
34
7.4
26
7.9
34
Financial Planning
7.8
10
Not enough data
8.2
10
Not enough data
8.5
10
Not enough data
Agentic AI - FP&A (Financial Planning & Analysis)
Not enough data
Not enough data
Not enough data
Not enough data
Financial Insight
8.0
10
Not enough data
8.8
10
Not enough data
7.9
11
Not enough data
Data
8.6
11
Not enough data
8.5
10
Not enough data
8.2
10
Not enough data
8.5
10
Not enough data
Status Communication
7.8
10
Not enough data
8.3
11
Not enough data
8.2
11
Not enough data
8.5
11
Not enough data
Management
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
Not enough data
Maintenance
8.8
25
Not enough data
8.9
25
Not enough data
9.1
25
Not enough data
Security
9.0
27
Not enough data
8.6
26
Not enough data
Integration
8.0
20
Not enough data
8.2
19
Not enough data
Business Logic
7.5
19
Not enough data
7.3
19
Not enough data
8.2
19
Not enough data
Management
7.7
18
Not enough data
7.5
19
Not enough data
Analytics
8.4
20
Not enough data
7.6
19
Not enough data
Deployment
8.2
19
Not enough data
7.6
17
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Agentic AI - Decision Management Platforms
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
Not enough data
Setup
7.7
19
Not enough data
7.5
19
Not enough data
8.0
19
Not enough data
Data
8.3
20
Not enough data
8.6
19
Not enough data
Analysis
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
Not enough data
Customization
7.6
18
Not enough data
7.5
19
Not enough data
8.1
19
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
8.9
28
Not enough data
8.6
28
Not enough data
8.5
28
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
7.8
28
Not enough data
7.9
28
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.4
28
Not enough data
8.1
28
Not enough data
8.3
28
Security and Compliance - Generative AI Infrastructure
Not enough data
8.6
28
Not enough data
8.5
28
Not enough data
8.9
28
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
8.3
28
Integration - Machine Learning
8.2
34
8.5
67
Learning - Machine Learning
8.4
36
8.5
66
8.4
36
8.3
65
8.5
35
8.8
66
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
8.9
23
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Not enough data
8.9
22
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
22
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.7
21
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
21
Not enough data
8.8
21
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.0
21
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.9
22
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
Not enough data
8.5
27
Not enough data
7.6
27
Not enough data
8.3
26
Functionality - AI Agent Builders
Not enough data
8.1
27
Not enough data
7.3
27
Not enough data
8.2
26
Not enough data
7.2
27
Data and Analytics - AI Agent Builders
Not enough data
7.7
25
Not enough data
7.9
27
Not enough data
8.0
27
Integration - AI Agent Builders
Not enough data
8.7
27
Not enough data
8.0
27
Not enough data
8.0
27
Not enough data
7.5
27
Agentic AI - Accounting & Finance
Not enough data
Not enough data
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
8.7
14
Not enough data
8.8
14
Not enough data
9.0
14
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
9.0
14
Not enough data
8.9
14
Not enough data
8.7
14
Not enough data
Statistical Tool
8.6
66
Not enough data
8.7
67
Not enough data
8.6
67
Not enough data
Data Analysis
8.9
66
Not enough data
8.8
66
Not enough data
Decision Making
8.7
67
Not enough data
9.0
68
Not enough data
8.8
67
Not enough data
8.6
67
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Functionality
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
Not enough data
Management
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
Not enough data
Generative AI
8.2
59
Not enough data
8.2
60
Not enough data
Building Reports
8.5
198
Not enough data
8.5
197
Not enough data
7.8
192
Not enough data
7.9
193
Not enough data
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
SAS Viya and Vertex AI are categorized as MLOps Platforms, Data Science and Machine Learning Platforms, Machine Learning, and Low-Code Machine Learning Platforms
Unique Categories
Vertex AI is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, and AI Agent Builders
Reviews
Reviewers' Company Size
SAS Viya
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Vertex AI
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
Pharmaceuticals
13.8%
Higher Education
9.1%
Banking
8.4%
Financial Services
6.6%
Information Technology and Services
6.3%
Other
55.8%
Computer Software
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.3%
Alternatives
Discussions
SAS Viya has no discussions with answers
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