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At a Glance
Market Segments
Mid-Market (44.0% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
Red Hat OpenShift Data Science
Star Rating
(25)4.4 out of 5
Market Segments
Mid-Market (44.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Red Hat OpenShift Data ScienceVertex AI
Star Rating
(592)4.3 out of 5
Market Segments
Small-Business (41.0% 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.
- Users report that Vertex AI excels in AI High Availability with a score of 9.2, which reviewers mention contributes to a more reliable infrastructure for deploying machine learning models compared to Red Hat OpenShift Data Science, which scored 8.5 in this area.
- Reviewers mention that Red Hat OpenShift Data Science offers superior Language Support with a score of 9.1, while Vertex AI scored 8.3, indicating that users find Red Hat's capabilities more robust for multilingual applications.
- G2 users highlight that Vertex AI's AI Inference Speed, rated at 8.6, is a significant advantage, as it allows for faster model predictions, whereas Red Hat OpenShift Data Science's performance in this area is slightly lower at 8.5.
- Users on G2 report that Red Hat OpenShift Data Science shines in its Data Ingestion & Wrangling capabilities, scoring 8.9, which reviewers say makes it easier to prepare data for analysis compared to Vertex AI's score of 8.3.
- Reviewers mention that Vertex AI's Model Training capabilities, rated at 8.5, are highly regarded, but Red Hat OpenShift Data Science edges out with a score of 8.6, indicating a preference for its training features among users.
- Users say that Red Hat OpenShift Data Science's Monitoring features, with a score of 8.5, provide better oversight of model performance, while Vertex AI's score of 8.6 suggests it still offers solid monitoring but may not be as comprehensive.
Pricing
Entry-Level Pricing
Red Hat OpenShift Data Science
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
Red Hat OpenShift Data Science
No trial information availableVertex AI
Free Trial is available
Ratings
Meets Requirements
8.8
23
8.6
359
Ease of Use
8.5
23
8.2
368
Ease of Setup
Not enough data
8.1
291
Ease of Admin
Not enough data
7.9
141
Quality of Support
8.6
21
8.1
335
Has the product been a good partner in doing business?
Not enough data
8.2
135
Product Direction (% positive)
10.0
23
9.2
353
Features by Category
Deployment
Not enough data
8.3
73
Not enough data
8.1
74
Not enough data
8.3
74
Not enough data
8.3
70
Not enough data
8.8
70
Deployment
Not enough data
8.4
73
Not enough data
8.3
72
Not enough data
8.4
71
Not enough data
8.5
71
Not enough data
8.7
69
Management
Not enough data
8.3
70
Not enough data
8.5
69
Not enough data
8.0
69
Not enough data
8.1
69
Operations
Not enough data
8.2
69
Not enough data
8.4
70
Not enough data
8.3
70
Management
Not enough data
8.1
68
Not enough data
8.4
69
Not enough data
8.3
68
Generative AI
Not enough data
8.2
34
Not enough data
8.4
34
System
8.9
22
8.2
170
Model Development
8.8
23
8.4
202
8.8
23
7.9
179
8.7
23
8.4
200
8.6
23
8.5
202
Model Development
8.8
23
8.2
165
Machine/Deep Learning Services
8.5
22
8.2
200
8.3
20
8.4
196
8.6
20
8.2
195
8.3
20
8.2
178
Machine/Deep Learning Services
8.6
20
8.5
165
8.7
21
8.4
163
Deployment
8.6
22
8.2
193
8.8
22
8.3
194
8.5
22
8.5
193
Generative AI
8.3
5
8.3
102
8.7
5
8.2
102
8.7
5
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.8
34
Not enough data
7.7
34
Not enough data
7.8
34
Not enough data
8.4
34
Not enough data
7.8
34
Not enough data
7.9
34
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
Not enough data
8.5
67
Learning - Machine Learning
Not enough data
8.5
66
Not enough data
8.3
65
Not enough data
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
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Red Hat OpenShift Data Science and Vertex AI are categorized as Data Science and Machine Learning Platforms
Unique Categories
Red Hat OpenShift Data Science has no unique categories
Vertex AI is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, MLOps Platforms, Machine Learning, AI Agent Builders, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Red Hat OpenShift Data Science
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
Market Research
32.0%
Marketing and Advertising
20.0%
Information Technology and Services
8.0%
Computer Software
8.0%
Transportation/Trucking/Railroad
4.0%
Other
28.0%
Computer Software
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.4%
Alternatives
Discussions
Red Hat OpenShift Data Science has no discussions with answers
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What is Google AI platform?
1 Comment
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The Google AI Platform is a comprehensive set of tools and services provided by Google Cloud to develop, deploy, and manage artificial intelligence. It...Read more
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