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Compare Azure Data Lake Analytics and Google Cloud BigQuery 
Featured Products
At a Glance
Market Segments
Enterprise (44.4% of reviews)
Enterprise (38.1% of reviews)
Entry-Level Pricing
No pricing available
Free
Azure Data Lake Analytics
Star Rating
(37)4.2 out of 5
Market Segments
Enterprise (44.4% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Azure Data Lake AnalyticsGoogle Cloud BigQuery
Star Rating
(1,208)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 plansSummary
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 Azure Data Lake Analytics. 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 intuitive onboarding, allowing users to quickly get started without extensive setup. In contrast, Azure Data Lake Analytics, while noted for its simplicity, has fewer recent reviews, which may indicate less current user engagement.
- Users say that Google Cloud BigQuery's performance is outstanding, with the ability to handle billions of queries efficiently. This is highlighted by feedback emphasizing its pay-as-you-go model, which simplifies operations and encourages experimentation with larger datasets, a feature that some Azure users find less flexible.
- Reviewers mention that Azure Data Lake Analytics offers a strong solution for data processing across various industries, particularly with its support for multiple processing languages like U-SQL, R, and Python. However, it lacks the same level of recent user feedback, which may affect potential buyers' confidence in its current capabilities.
- G2 reviewers highlight that Google Cloud BigQuery's ease of use is a significant advantage, with users rating it highly for its data querying capabilities. In comparison, while Azure Data Lake Analytics also receives good marks, it falls slightly behind in user experience, indicating that BigQuery may be more user-friendly for everyday tasks.
- According to recent user feedback, both platforms offer solid data visualization tools, but Google Cloud BigQuery's integration with AI tooling and its advanced analytics features give it an edge. Users appreciate the seamless integration of these tools, which enhances their data analysis capabilities compared to Azure's offerings.
Pricing
Entry-Level Pricing
Azure Data Lake Analytics
No pricing availableGoogle 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
Free Trial
Azure Data Lake Analytics
No trial information availableGoogle Cloud BigQuery
Free Trial is available
Ratings
Meets Requirements
8.6
23
8.8
616
Ease of Use
8.4
23
8.7
632
Ease of Setup
8.3
11
8.8
407
Ease of Admin
8.3
11
8.5
224
Quality of Support
8.5
23
8.4
565
Has the product been a good partner in doing business?
8.6
11
8.6
217
Product Direction (% positive)
9.0
24
9.3
605
Features by Category
Management
Not enough data
8.6
121
Not enough data
8.3
119
Functionality
Not enough data
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
Data Management
Not enough data
8.9
220
|
Verified
Not enough data
8.3
210
|
Verified
Not enough data
8.9
215
|
Verified
Not enough data
8.6
215
|
Verified
Not enough data
8.3
203
|
Verified
Not enough data
8.7
200
|
Verified
Integration
Not enough data
8.5
202
|
Verified
Not enough data
8.6
213
|
Verified
Not enough data
8.6
200
|
Verified
Deployment
Not enough data
7.7
186
|
Verified
Not enough data
9.1
216
|
Verified
Performance
Not enough data
9.1
224
|
Verified
Security
Not enough data
8.7
207
|
Verified
Not enough data
9.1
213
|
Verified
Generative AI
Not enough data
7.6
127
Not enough data
7.8
124
Storage
Not enough data
9.1
70
Not enough data
8.8
70
Availability
Not enough data
8.4
62
Not enough data
8.5
66
Not enough data
8.6
68
Performance
Not enough data
8.5
65
Security
Not enough data
8.7
70
Not enough data
8.8
69
Not enough data
8.4
69
Not enough data
8.7
65
Support
Not enough data
8.7
66
Not enough data
8.9
66
Centralized computation
Not enough data
9.1
27
Localized computation
Not enough data
8.5
28
Statistical Tool
Not enough data
8.7
78
Not enough data
9.0
78
Not enough data
8.8
79
Data Analysis
Not enough data
9.3
78
Not enough data
9.1
79
Decision Making
Not enough data
8.8
79
Not enough data
8.7
77
Not enough data
8.7
79
Not enough data
8.7
77
Generative AI
Not enough data
7.5
50
Not enough data
7.8
50
Marketing Operations
Not enough data
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
Campaign Activity
Not enough data
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
Agentic AI - Marketing Analytics
Not enough data
8.7
15
Not enough data
9.6
15
Not enough data
8.2
15
Database
Not enough data
8.8
175
Not enough data
8.9
173
Not enough data
8.7
167
Integrations
Not enough data
8.4
136
Not enough data
8.5
133
Platform
Not enough data
8.9
151
Not enough data
8.9
165
Not enough data
8.5
133
Processing
Not enough data
9.2
168
Not enough data
9.1
161
Data Transformation
8.1
17
|
Verified
8.8
283
8.8
16
|
Verified
9.3
293
Connectivity
8.4
18
|
Verified
8.1
251
8.6
17
|
Verified
8.2
249
7.9
19
|
Verified
8.7
278
9.0
20
|
Verified
8.7
269
Operations
8.5
19
|
Verified
8.5
278
8.5
17
|
Verified
8.7
277
8.1
18
|
Verified
8.3
255
8.9
16
|
Verified
8.4
262
8.2
15
|
Verified
8.5
254
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
Azure Data Lake Analytics and Google Cloud BigQuery are categorized as Big Data Analytics
Unique Categories
Azure Data Lake Analytics has no unique categories
Google Cloud BigQuery is categorized as Columnar Databases, Big Data Integration Platforms, ETL Tools, Big Data Processing and Distribution, Marketing Analytics, Predictive Analytics, Data Warehouse, and Data Clean Room
Reviews
Reviewers' Company Size
Azure Data Lake Analytics
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Google Cloud BigQuery
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
Computer Software
14.8%
Consumer Goods
11.1%
Telecommunications
7.4%
Internet
7.4%
Information Technology and Services
7.4%
Other
51.9%
Information Technology and Services
16.2%
Computer Software
13.5%
Retail
7.1%
Financial Services
6.4%
Marketing and Advertising
5.1%
Other
51.7%
Alternatives
Discussions
Azure Data Lake Analytics has no discussions with answers
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
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