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Compare AWS Bedrock and Vertex AI 
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At a Glance
Market Segments
Enterprise (38.6% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
AWS Bedrock
Star Rating
(44)4.4 out of 5
Market Segments
Enterprise (38.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about AWS BedrockVertex 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 service for critical applications, while AWS Bedrock scores lower at 8.6, indicating potential concerns for users needing consistent uptime.
- Reviewers mention that Vertex AI's AI Inference Speed is rated at 8.6, providing faster responses for real-time applications, whereas AWS Bedrock's score of 8.1 suggests it may not be as efficient in delivering quick results, which could impact user experience.
- G2 users highlight that Vertex AI offers robust AI Data Encryption tools with a score of 9.2, ensuring higher security for sensitive data, while AWS Bedrock's lower score of 7.6 raises concerns about its data protection capabilities.
- Users on G2 report that Vertex AI's model training capabilities are well-regarded, with a score of 8.5, allowing for effective customization and optimization, while AWS Bedrock matches this score but lacks specific user testimonials that highlight standout features in this area.
- Reviewers mention that Vertex AI's AI Cost per API Call is rated at 8.0, which some users find to be more economical for their needs compared to AWS Bedrock's score of 8.1, suggesting that cost efficiency may vary based on usage patterns.
- Users say that Vertex AI's documentation quality is rated at 8.5, which many find helpful for onboarding and troubleshooting, while AWS Bedrock's score of 8.1 indicates that users may encounter challenges due to less comprehensive support resources.
Pricing
Entry-Level Pricing
AWS Bedrock
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
AWS Bedrock
No trial information availableVertex AI
Free Trial is available
Ratings
Meets Requirements
8.6
44
8.6
359
Ease of Use
8.1
44
8.2
368
Ease of Setup
8.4
43
8.1
291
Ease of Admin
9.0
15
7.9
141
Quality of Support
8.5
43
8.1
335
Has the product been a good partner in doing business?
8.5
14
8.2
135
Product Direction (% positive)
9.5
43
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
Not enough data
8.2
170
Model Development
Not enough data
8.4
202
Not enough data
7.9
179
Not enough data
8.4
200
Not enough data
8.5
202
Model Development
Not enough data
8.2
165
Machine/Deep Learning Services
Not enough data
8.2
200
Not enough data
8.4
196
Not enough data
8.2
195
Not enough data
8.2
178
Machine/Deep Learning Services
Not enough data
8.5
165
Not enough data
8.4
163
Deployment
Not enough data
8.2
193
Not enough data
8.3
194
Not enough data
8.5
193
Generative AI
Not enough data
8.3
102
Not enough data
8.2
102
Not enough data
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
8.9
14
8.9
28
8.5
13
8.6
28
8.2
14
8.5
28
Cost and Efficiency - Generative AI Infrastructure
8.1
14
8.2
28
8.5
14
7.8
28
7.9
14
7.9
28
Integration and Extensibility - Generative AI Infrastructure
8.6
14
8.4
28
8.8
14
8.1
28
8.2
14
8.3
28
Security and Compliance - Generative AI Infrastructure
8.6
14
8.6
28
8.7
14
8.5
28
8.5
14
8.9
28
Usability and Support - Generative AI Infrastructure
7.7
14
8.2
28
7.7
14
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
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.0
5
8.8
22
7.3
5
8.9
22
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
8.7
5
9.2
22
Custom Training - Large Language Model Operationalization (LLMOps)
7.7
5
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
8.3
5
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)
9.0
5
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
7.9
7
8.5
27
7.6
7
7.6
27
7.7
8
8.3
26
Functionality - AI Agent Builders
7.5
8
8.1
27
7.4
7
7.3
27
7.4
7
8.2
26
8.1
7
7.2
27
Data and Analytics - AI Agent Builders
8.1
7
7.7
25
8.1
7
7.9
27
9.3
7
8.0
27
Integration - AI Agent Builders
8.3
7
8.7
27
8.3
7
8.0
27
7.9
7
8.0
27
7.5
6
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
AWS Bedrock and Vertex AI are categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, and AI Agent Builders
Unique Categories
AWS Bedrock has no unique categories
Vertex AI is categorized as MLOps Platforms, Data Science and Machine Learning Platforms, Machine Learning, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
AWS Bedrock
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
Information Technology and Services
22.7%
Computer Software
18.2%
Financial Services
6.8%
Consulting
4.5%
Retail
4.5%
Other
43.2%
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
AWS Bedrock has no discussions with answers
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KS
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What software libraries does cloud ML engine support?
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It's supporting approx all trending libraries.Read more
What is Google AI platform?
1 Comment
ZM
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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