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Compare Google Cloud BigQuery and IBM Cloud Pak for Data 
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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
(1,201)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 plansIBM Cloud Pak for Data
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (50.0% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Cloud Pak for DataSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Google Cloud BigQuery excels in data ingestion and wrangling with a score of 9.5, making it a preferred choice for handling large datasets efficiently. In contrast, IBM Cloud Pak for Data, while robust, has not received the same level of acclaim in this area, indicating a potential gap in user experience.
- Reviewers mention that Google Cloud BigQuery's real-time analytics capabilities are highly rated at 8.8, allowing for immediate insights. Users on G2 note that IBM Cloud Pak for Data, with a score of 8.5, offers solid performance but may not match the immediacy that BigQuery provides.
- G2 users highlight the customization options in Google Cloud BigQuery, particularly its ability to support custom VMs with a score of 8.0. In comparison, IBM Cloud Pak for Data's customization features are perceived as less flexible, which could limit user adaptability in specific scenarios.
- Users say that Google Cloud BigQuery's data query performance is exceptional, scoring 9.3, which is crucial for businesses needing quick data retrieval. Conversely, IBM Cloud Pak for Data, while still strong at 9.1, may not deliver the same speed, which could impact time-sensitive decision-making.
- Reviewers mention that Google Cloud BigQuery's AI and machine learning integration is robust, with a score of 8.5, making it easier for users to implement advanced analytics. IBM Cloud Pak for Data, while offering good integration, scores slightly lower, indicating that users may find BigQuery more conducive for AI-driven projects.
- Users report that Google Cloud BigQuery's ease of setup is rated at 8.6, making it user-friendly for new adopters. In contrast, IBM Cloud Pak for Data's score of 7.2 suggests that users may face more challenges during initial implementation, which could deter potential customers.
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
612
8.5
47
Ease of Use
8.7
626
8.1
47
Ease of Setup
8.8
401
7.2
26
Ease of Admin
8.5
224
7.6
27
Quality of Support
8.4
564
8.3
42
Has the product been a good partner in doing business?
8.7
217
8.1
25
Product Direction (% positive)
9.2
600
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
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
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
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
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
79
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
80
8.3
6
8.7
78
8.8
7
8.7
80
8.8
8
8.7
78
8.3
8
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
8.5
27
|
Verified
9.3
295
9.1
15
|
Verified
Connectivity
8.1
256
8.0
23
|
Verified
8.2
254
8.6
22
|
Verified
8.7
283
8.1
25
|
Verified
8.8
274
8.7
24
|
Verified
Operations
8.5
283
8.7
26
|
Verified
8.7
282
8.9
25
|
Verified
8.3
260
8.4
23
|
Verified
8.4
267
8.8
24
|
Verified
8.5
259
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
16.2%
Computer Software
13.5%
Retail
7.1%
Financial Services
6.5%
Marketing and Advertising
5.1%
Other
51.7%
Computer Software
12.9%
Information Technology and Services
8.6%
Banking
8.6%
Financial Services
5.7%
Education Management
5.7%
Other
58.6%
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
IBM Cloud Pak for Data has no discussions with answers
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