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Compare Apache Spark for Azure HDInsight and Google Cloud BigQuery 
Featured Products
At a Glance
Market Segments
Mid-Market (63.6% of reviews)
Enterprise (38.1% of reviews)
Entry-Level Pricing
No pricing available
Free
Apache Spark for Azure HDInsight
Star Rating
(12)4.0 out of 5
Market Segments
Mid-Market (63.6% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache Spark for Azure HDInsightGoogle 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 high G2 Score of 98.37, which reflects its strong performance and positive feedback from a large number of users. In contrast, Apache Spark for Azure HDInsight has a significantly lower score of 38.36, indicating challenges in meeting user expectations.
- Users say that BigQuery's serverless architecture simplifies data analysis, allowing them to focus on writing clean SQL without the hassle of managing infrastructure. This feature is particularly praised for its efficiency in handling billions of queries, making it a preferred choice for enterprises.
- Reviewers mention that Apache Spark for Azure HDInsight offers a clean and intuitive environment for data analytics, which some users appreciate. However, the overall lack of recent reviews (only 12 compared to BigQuery's 1125) suggests that it may not be as widely adopted or supported in the current market.
- According to verified reviews, BigQuery's pay-as-you-go model is a standout feature, allowing users to only pay for the storage and compute resources they actually use. This flexibility is particularly beneficial for organizations looking to experiment with larger datasets without incurring unnecessary costs.
- Users highlight that while Apache Spark for Azure HDInsight provides good performance for data analytics, it faces challenges in overall user satisfaction compared to BigQuery. The latter's higher ratings in ease of use and setup indicate a smoother experience for users, which is crucial for day-to-day operations.
- Reviewers appreciate BigQuery's integration with advanced AI tooling, which enhances its capabilities for machine learning and data processing. This integration is a significant advantage for users looking to leverage cutting-edge technology in their data workflows, setting BigQuery apart from its competitors.
Pricing
Entry-Level Pricing
Apache Spark for Azure HDInsight
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
Apache Spark for Azure HDInsight
No trial information availableGoogle Cloud BigQuery
Free Trial is available
Ratings
Meets Requirements
8.3
10
8.8
616
Ease of Use
8.5
10
8.7
632
Ease of Setup
Not enough data
8.8
407
Ease of Admin
Not enough data
8.5
224
Quality of Support
8.3
10
8.4
565
Has the product been a good partner in doing business?
Not enough data
8.6
217
Product Direction (% positive)
8.8
10
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
8.9
9
8.8
175
8.3
9
8.9
173
8.9
9
8.7
167
Integrations
9.4
9
8.4
136
8.9
9
8.5
133
Platform
8.7
9
8.9
151
8.3
9
8.9
165
8.9
9
8.5
133
Processing
8.7
9
9.2
168
8.1
9
9.1
161
Data Transformation
Not enough data
8.8
283
Not enough data
9.3
293
Connectivity
Not enough data
8.1
251
Not enough data
8.2
249
Not enough data
8.7
278
Not enough data
8.7
269
Operations
Not enough data
8.5
278
Not enough data
8.7
277
Not enough data
8.3
255
Not enough data
8.4
262
Not enough data
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
Apache Spark for Azure HDInsight and Google Cloud BigQuery are categorized as Big Data Processing and Distribution
Unique Categories
Apache Spark for Azure HDInsight has no unique categories
Google Cloud BigQuery is categorized as Columnar Databases, Big Data Integration Platforms, ETL Tools, Big Data Analytics, Marketing Analytics, Predictive Analytics, Data Warehouse, and Data Clean Room
Reviews
Reviewers' Company Size
Apache Spark for Azure HDInsight
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
Research
9.1%
Machinery
9.1%
Luxury Goods & Jewelry
9.1%
Information Technology and Services
9.1%
Higher Education
9.1%
Other
54.5%
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
Apache Spark for Azure HDInsight 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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