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Compare Google Cloud BigQuery and IBM Watson Studio 
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At a Glance
Market Segments
Enterprise (38.1% of reviews)
Enterprise (51.3% 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 Watson Studio
Star Rating
(164)4.2 out of 5
Market Segments
Enterprise (51.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Watson StudioSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Google Cloud BigQuery excels in data source access, with a score of 8.9 for breadth of data sources and 9.3 for ease of data connectivity, making it easier to integrate various data sources seamlessly. In contrast, IBM Watson Studio, while strong, has lower scores in these areas, indicating potential challenges in connecting to diverse data sources.
- Reviewers mention that Google Cloud BigQuery's scalability is a standout feature, scoring 9.0, which allows users to handle large datasets efficiently. On the other hand, IBM Watson Studio, with a scalability score of 8.6, may not perform as well under heavy data loads, which could be a concern for enterprise users.
- G2 users highlight the ease of deployment in Google Cloud BigQuery, scoring 9.8, which is significantly higher than IBM Watson Studio's score of 9.5. This suggests that users find BigQuery more straightforward to set up and start using, which is crucial for teams looking to minimize downtime.
- Users on G2 report that Google Cloud BigQuery's data management capabilities are robust, particularly in data integration (9.0) and data quality (8.8). In contrast, IBM Watson Studio's scores in these areas are slightly lower, indicating that users may find BigQuery more reliable for maintaining data integrity.
- Reviewers mention that IBM Watson Studio shines in model development, particularly with pre-built algorithms (9.2) and feature engineering (9.4), which can significantly speed up the machine learning process. Google Cloud BigQuery, while strong in data analytics, does not focus as heavily on model development features.
- Users say that Google Cloud BigQuery's reporting capabilities are highly rated at 8.6, providing users with effective tools for data visualization and insights. In comparison, IBM Watson Studio's reporting features, while functional, score lower at 8.5, suggesting that users may find BigQuery's reporting tools more intuitive and effective for their needs.
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 Watson Studio
No pricing availableFree Trial
Google Cloud BigQuery
Free Trial is available
IBM Watson Studio
No trial information availableRatings
Meets Requirements
8.8
612
8.3
121
Ease of Use
8.7
626
8.0
122
Ease of Setup
8.8
401
7.6
100
Ease of Admin
8.5
224
7.8
95
Quality of Support
8.4
564
8.2
113
Has the product been a good partner in doing business?
8.7
217
8.0
94
Product Direction (% positive)
9.2
600
8.5
115
Features by Category
Data Source Access
Not enough data
9.0
13
Not enough data
9.3
12
Not enough data
9.2
14
Data Interaction
Not enough data
9.0
14
Not enough data
9.2
12
Not enough data
9.4
12
Not enough data
9.1
13
Not enough data
9.2
12
Not enough data
9.2
13
Not enough data
9.1
13
Not enough data
9.6
12
Data Exporting
Not enough data
9.4
12
Not enough data
9.2
12
Not enough data
9.2
12
Generative AI
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
Deployment
Not enough data
8.8
8
Not enough data
9.2
8
Not enough data
9.0
8
Not enough data
9.4
8
Not enough data
8.8
8
Deployment
Not enough data
9.0
8
Not enough data
8.8
8
Not enough data
8.8
8
Not enough data
9.4
8
Not enough data
9.2
8
Management
Not enough data
9.3
7
Not enough data
9.6
8
Not enough data
9.0
7
Not enough data
9.0
8
Operations
Not enough data
9.0
8
Not enough data
9.0
8
Not enough data
9.3
7
Management
Not enough data
9.5
7
Not enough data
9.4
8
Not enough data
8.8
7
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
Not enough data
9.0
12
Model Development
Not enough data
8.5
33
Not enough data
8.8
34
Not enough data
8.5
35
Not enough data
8.3
36
Model Development
Not enough data
9.4
13
Machine/Deep Learning Services
Not enough data
8.5
27
Not enough data
8.5
34
Not enough data
Feature Not Available
Not enough data
8.6
28
Machine/Deep Learning Services
Not enough data
8.9
12
Not enough data
9.0
12
Deployment
Not enough data
8.5
32
Not enough data
8.6
33
Not enough data
8.6
30
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
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
Setup
Not enough data
8.6
7
Not enough data
8.3
7
Not enough data
9.7
6
Data
Not enough data
8.6
7
Not enough data
8.6
7
Analysis
Not enough data
9.7
6
Not enough data
8.1
7
Not enough data
8.1
7
Not enough data
8.3
7
Not enough data
8.8
7
Not enough data
8.1
7
Not enough data
7.9
7
Customization
Not enough data
9.0
7
Not enough data
8.1
7
Not enough data
9.2
6
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Centralized computation
9.1
27
Not enough data
Localized computation
8.5
28
Not enough data
Statistical Tool
8.7
78
8.0
14
9.0
79
8.4
15
8.8
79
8.1
15
Data Analysis
9.3
78
8.7
15
9.1
79
9.0
14
Decision Making
8.8
80
8.6
14
8.7
78
8.6
15
8.7
80
8.3
13
8.7
78
8.7
14
Generative AI
7.5
51
9.3
5
7.8
51
8.3
5
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 IBM Watson Studio are categorized as Predictive Analytics
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, Data Warehouse, and Data Clean Room
IBM Watson Studio is categorized as Text Analysis, Data Science and Machine Learning Platforms, MLOps Platforms, and Data Preparation
Reviews
Reviewers' Company Size
Google Cloud BigQuery
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Watson Studio
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%
Information Technology and Services
15.8%
Computer Software
13.3%
Telecommunications
8.2%
Banking
7.6%
Education Management
5.7%
Other
49.4%
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
IBM Watson Studio has no discussions with answers
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