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Compare Google Cloud BigQuery and Vertex AI 
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At a Glance
Market Segments
Enterprise (38.1% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
Free
Pay As You Go Per Month
Google Cloud BigQuery
Star Rating
(1,203)4.5 out of 5
Market Segments
Enterprise (38.1% of reviews)
Pros & Cons
Entry-Level Pricing
Free
Free Trial is available
Browse all 5 pricing plansVertex 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 AIGoogle Cloud BigQuery vs Vertex AI
When assessing the two solutions, reviewers found Google Cloud BigQuery easier to use, set up, and administer. Reviewers also preferred doing business with Google Cloud BigQuery overall.
- Reviewers felt that Google Cloud BigQuery meets the needs of their business better than Vertex AI.
- When comparing quality of ongoing product support, reviewers felt that Google Cloud BigQuery is the preferred option.
- When assessing product direction, Google Cloud BigQuery and Vertex AI received similar ratings from our reviewers.
Pricing
Entry-Level Pricing
Google Cloud BigQuery
Free
Free
New customers get $300 in free Google Cloud credits to spend on BigQuery with free trial sign-up.
- 10 GB storage
- Up to 1 TB queries per month
Vertex 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
Google Cloud BigQuery
Free Trial is available
Vertex AI
Free Trial is available
Ratings
Meets Requirements
8.8
612
8.6
359
Ease of Use
8.7
626
8.2
368
Ease of Setup
8.8
401
8.1
291
Ease of Admin
8.5
224
7.9
141
Quality of Support
8.4
564
8.1
335
Has the product been a good partner in doing business?
8.7
217
8.2
135
Product Direction (% positive)
9.2
600
9.2
353
Features by Category
Management
8.6
123
Not enough data
8.3
121
Not enough data
Functionality
9.0
121
Not enough data
9.1
124
Not enough data
9.0
124
Not enough data
8.9
123
Not enough data
9.4
124
Not enough data
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
Data Management
8.9
223
|
Verified
Not enough data
8.3
214
|
Verified
Not enough data
8.9
219
|
Verified
Not enough data
8.6
215
|
Verified
Not enough data
8.3
204
|
Verified
Not enough data
8.7
205
|
Verified
Not enough data
Integration
8.6
204
|
Verified
Not enough data
8.6
216
|
Verified
Not enough data
8.6
204
|
Verified
Not enough data
Deployment
7.8
190
|
Verified
Not enough data
9.1
215
|
Verified
Not enough data
Performance
9.1
220
|
Verified
Not enough data
Security
8.7
211
|
Verified
Not enough data
9.2
217
|
Verified
Not enough data
Generative AI
7.7
132
Not enough data
7.9
129
Not enough data
Storage
9.1
70
Not enough data
8.8
70
Not enough data
Availability
8.4
62
Not enough data
8.5
66
Not enough data
8.6
68
Not enough data
Performance
8.5
65
Not enough data
Security
8.7
70
Not enough data
8.8
69
Not enough data
8.4
69
Not enough data
8.7
65
Not enough data
Support
8.7
66
Not enough data
8.9
66
Not enough data
Centralized computation
9.1
27
Not enough data
Localized computation
8.5
28
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
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
Statistical Tool
8.7
78
Not enough data
9.0
79
Not enough data
8.8
79
Not enough data
Data Analysis
9.3
78
Not enough data
9.1
79
Not enough data
Decision Making
8.8
80
Not enough data
8.7
78
Not enough data
8.7
80
Not enough data
8.7
78
Not enough data
Generative AI
7.5
51
Not enough data
7.8
51
Not enough data
Marketing Operations
8.8
66
Not enough data
9.2
64
Not enough data
8.9
65
Not enough data
9.4
66
Not enough data
8.8
63
Not enough data
8.5
63
Not enough data
Campaign Activity
9.1
68
Not enough data
9.5
67
Not enough data
8.7
64
Not enough data
9.2
62
Not enough data
8.9
63
Not enough data
9.1
65
Not enough data
Agentic AI - Marketing Analytics
8.8
16
Not enough data
9.6
16
Not enough data
8.3
16
Not enough data
Database
8.8
178
Not enough data
8.9
176
Not enough data
8.8
170
Not enough data
Integrations
8.4
139
Not enough data
8.6
136
Not enough data
Platform
8.9
153
Not enough data
8.9
168
Not enough data
8.6
136
Not enough data
Processing
9.3
170
Not enough data
9.1
164
Not enough data
Data Transformation
8.8
288
Not enough data
9.3
295
Not enough data
Connectivity
8.1
256
Not enough data
8.2
254
Not enough data
8.7
283
Not enough data
8.8
274
Not enough data
Operations
8.5
283
Not enough data
8.7
282
Not enough data
8.3
260
Not enough data
8.4
267
Not enough data
8.5
259
Not enough data
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
Google Cloud BigQuery and Vertex AI share no categories
Unique Categories
Google Cloud BigQuery is categorized as Columnar Databases, Big Data Integration Platforms, ETL Tools, Big Data Processing and Distribution, Big Data Analytics, Marketing Analytics, Predictive Analytics, Data Warehouse, and Data Clean Room
Reviews
Reviewers' Company Size
Google Cloud BigQuery
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
16.2%
Computer Software
13.5%
Retail
7.1%
Financial Services
6.5%
Marketing and Advertising
5.1%
Other
51.7%
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
Is Big Query free?
3 Comments
BG
noRead more
Is BigQuery part of Google Cloud Platform?
2 Comments
AY
Yes, Bigquery is a GCP product and a serveless data wharehouse.Read more
How BQ legacy SQl is different form the standard SQL?
1 Comment
OD
Legacy SQL is a non-standard SQL only used by BigQuery. Standard SQL is compliant with the SQL 2011.
Google recommends using Standard SQL and looking at the...Read more
What is Google Cloud AI Platform used for?
2 Comments
KS
Google cloud AI Platform enables us to build Machine learning models, that works on any type and any size of data. Read more
What software libraries does cloud ML engine support?
2 Comments
JP
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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