Compare Google Cloud BigQuery and IBM Cloud Pak for Data 
At a Glance
Market Segments
Enterprise (38.1% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
Free
No pricing available
Google Cloud BigQuery
Star Rating
(1,224)4.5 out of 5
Market Segments
Enterprise (38.1% of reviews)
Pros & Cons
Entry-Level Pricing
Free
Browse all 5 pricing plansIBM Cloud Pak for Data
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (50.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about IBM Cloud Pak for DataSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Google Cloud BigQuery excels in user satisfaction, boasting a significantly higher overall score compared to IBM Cloud Pak for Data. Users appreciate its serverless architecture and the ability to focus on SQL without worrying about infrastructure, making data analysis feel smooth and efficient.
- According to verified reviews, Google Cloud BigQuery's implementation process is praised for its simplicity and speed. Users highlight the pay-as-you-go model that allows for experimentation with larger datasets without the need for provisioning clusters, which is a major advantage over IBM Cloud Pak for Data.
- Reviewers mention that while IBM Cloud Pak for Data offers a comprehensive approach to data management and analytics, it faces challenges in user experience. Some users find it less intuitive compared to BigQuery, despite its strengths in unifying siloed data and facilitating data analysis workflows.
- Users say that Google Cloud BigQuery's performance in handling large queries is exceptional, with one reviewer noting it can solve billions of queries efficiently. This capability positions it as a strong choice for enterprises needing robust data analytics solutions.
- G2 reviewers highlight that IBM Cloud Pak for Data has an intuitive user interface that integrates well with Watson AI services, which can be beneficial for organizations focused on AI-driven analytics. However, some users feel that it does not match the speed and efficiency of BigQuery.
- According to recent user feedback, Google Cloud BigQuery's ease of use is a standout feature, with users noting its ability to simplify complex data tasks. In contrast, IBM Cloud Pak for Data, while powerful, may require more effort to navigate and utilize effectively.
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
IBM Cloud Pak for Data
No pricing availableFree Trial
Google Cloud BigQuery
Free Trial is available
IBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.8
626
8.5
47
Ease of Use
8.7
642
8.1
47
Ease of Setup
8.7
416
7.2
26
Ease of Admin
8.5
227
7.6
27
Quality of Support
8.3
573
8.3
42
Has the product been a good partner in doing business?
8.6
220
8.1
25
Product Direction (% positive)
9.3
614
8.8
47
Features by Category
Customization
Not enough data
8.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure
Not enough data
Not enough data
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
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
Management
8.6
121
Not enough data
8.3
119
Not enough data
Functionality
9.0
119
Not enough data
9.1
123
Not enough data
9.0
123
Not enough data
8.9
122
Not enough data
9.3
122
Not enough data
Infrastructure Provision
Not enough data
7.7
8
Not enough data
8.1
7
Not enough data
7.9
7
Not enough data
8.3
6
Not enough data
8.5
8
Not enough data
7.9
8
Not enough data
8.3
8
Not enough data
8.3
7
Management
Not enough data
8.6
7
Not enough data
8.3
7
Not enough data
8.1
8
Functionality
Not enough data
8.3
8
System
Not enough data
9.5
11
Model Development
Not enough data
8.3
8
Not enough data
8.5
8
Not enough data
9.1
9
Not enough data
8.8
8
Model Development
Not enough data
8.5
12
Machine/Deep Learning Services
Not enough data
8.7
9
Not enough data
9.4
8
Not enough data
9.6
8
Not enough data
9.0
7
Machine/Deep Learning Services
Not enough data
9.2
8
Not enough data
9.3
7
Deployment
Not enough data
9.3
9
Not enough data
9.3
9
Not enough data
8.9
9
Generative AI
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
8.3
5
Agentic AI - Data Science and Machine Learning Platforms
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
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
8.3
5
Analytics
Not enough data
Not enough data
Security
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Fabric
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
Data Management
8.9
224
|
Verified
Not enough data
8.3
210
|
Verified
Not enough data
8.9
215
|
Verified
Not enough data
8.6
219
|
Verified
Not enough data
8.3
204
|
Verified
Not enough data
8.6
201
|
Verified
Not enough data
Integration
8.5
202
|
Verified
Not enough data
8.6
214
|
Verified
Not enough data
8.6
201
|
Verified
Not enough data
Deployment
7.7
186
|
Verified
Not enough data
9.1
223
|
Verified
Not enough data
Performance
9.1
233
|
Verified
Not enough data
Security
8.7
208
|
Verified
Not enough data
9.2
214
|
Verified
Not enough data
Generative AI
7.6
127
Not enough data
7.8
124
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
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
8.7
78
8.3
5
9.0
78
8.8
8
8.8
79
8.6
7
Data Analysis
9.3
78
8.7
9
9.1
79
9.0
7
Decision Making
8.8
79
8.3
6
8.7
77
8.8
7
8.7
79
8.8
8
8.7
77
8.3
8
Generative AI
7.5
50
Not enough data
7.8
50
Not enough data
Marketing Operations
8.8
65
Not enough data
9.2
64
Not enough data
8.9
64
Not enough data
9.4
65
Not enough data
8.8
63
Not enough data
8.4
62
Not enough data
Campaign Activity
9.1
67
Not enough data
9.5
67
Not enough data
8.7
64
Not enough data
9.2
61
Not enough data
8.9
62
Not enough data
9.0
64
Not enough data
Agentic AI - Marketing Analytics
8.7
15
Not enough data
9.6
15
Not enough data
8.2
15
Not enough data
Database
8.8
175
Not enough data
8.9
173
Not enough data
8.7
167
Not enough data
Integrations
8.4
136
Not enough data
8.5
133
Not enough data
Platform
8.9
151
Not enough data
8.9
165
Not enough data
8.5
133
Not enough data
Processing
9.2
168
Not enough data
9.1
161
Not enough data
Data Transformation
8.8
283
8.5
27
|
Verified
9.3
293
9.1
15
|
Verified
Connectivity
8.1
251
8.0
23
|
Verified
8.2
249
8.6
22
|
Verified
8.7
278
8.1
25
|
Verified
8.7
269
8.7
24
|
Verified
Operations
8.5
279
8.7
26
|
Verified
8.7
277
8.9
25
|
Verified
8.3
255
8.4
23
|
Verified
8.4
262
8.8
24
|
Verified
8.5
254
8.7
13
|
Verified
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 IBM Cloud Pak for Data are categorized as Big Data Analytics and Predictive Analytics
Unique Categories
Google Cloud BigQuery is categorized as Columnar Databases, Big Data Integration Platforms, ETL Tools, Big Data Processing and Distribution, Marketing Analytics, Data Warehouse, and Data Clean Room
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Data Science and Machine Learning Platforms, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
Reviews
Reviewers' Company Size
Google Cloud BigQuery
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Cloud Pak for Data
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
16.1%
Computer Software
13.5%
Retail
7.0%
Financial Services
6.5%
Marketing and Advertising
5.2%
Other
51.7%
Computer Software
12.9%
Banking
8.6%
Information Technology and Services
8.6%
Education Management
5.7%
Financial Services
5.7%
Other
58.6%
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
IBM Cloud Pak for Data has no discussions with answers
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