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Compare Apache Parquet and Google Cloud BigQuery 
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At a Glance
Market Segments
Mid-Market (50.0% of reviews)
Enterprise (38.1% of reviews)
Entry-Level Pricing
No pricing available
Free
Apache Parquet
Star Rating
(27)4.3 out of 5
Market Segments
Mid-Market (50.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Apache ParquetGoogle Cloud BigQuery
Star Rating
(1,203)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.
- Users report that Google Cloud BigQuery excels in data integration with a score of 9.0, allowing seamless connections to various data sources, while Apache Parquet, although strong in data storage with a score of 9.0, lacks the same level of integration capabilities.
- Reviewers mention that Google Cloud BigQuery's real-time analytics feature, rated at 8.8, provides immediate insights, which is a significant advantage for businesses needing timely data, whereas Apache Parquet does not focus on real-time processing.
- G2 users highlight that Google Cloud BigQuery's ease of use is rated at 8.7, making it more user-friendly for non-technical users compared to Apache Parquet, which has a lower ease of use score of 7.7, indicating a steeper learning curve.
- Users on G2 report that Google Cloud BigQuery's quality of support is rated at 8.3, with many praising the responsiveness and helpfulness of the support team, while Apache Parquet's support, rated at 8.1, is seen as less comprehensive.
- Reviewers mention that Google Cloud BigQuery's scalability is a standout feature with a score of 9.3, allowing businesses to handle large datasets efficiently, while Apache Parquet, while capable, does not match this level of scalability.
- Users say that Google Cloud BigQuery's built-in data analytics feature, rated at 8.6, provides powerful tools for data analysis directly within the platform, whereas Apache Parquet is primarily a data storage format and lacks integrated analytics capabilities.
Pricing
Entry-Level Pricing
Apache Parquet
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 Parquet
No trial information availableGoogle Cloud BigQuery
Free Trial is available
Ratings
Meets Requirements
8.5
21
8.8
612
Ease of Use
7.7
22
8.7
626
Ease of Setup
7.2
9
8.8
401
Ease of Admin
7.6
9
8.5
224
Quality of Support
8.1
19
8.4
564
Has the product been a good partner in doing business?
7.5
8
8.7
217
Product Direction (% positive)
8.6
25
9.2
600
Features by Category
Management
Not enough data
8.6
123
Not enough data
8.3
121
Functionality
Not enough data
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
Data Management
Not enough data
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
Integration
Not enough data
8.6
204
|
Verified
Not enough data
8.6
216
|
Verified
Not enough data
8.6
204
|
Verified
Deployment
Not enough data
7.8
190
|
Verified
Not enough data
9.1
215
|
Verified
Performance
Not enough data
9.1
220
|
Verified
Security
Not enough data
8.7
211
|
Verified
Not enough data
9.2
217
|
Verified
Generative AI
Not enough data
7.7
132
Not enough data
7.9
129
Storage
9.0
13
9.1
70
8.8
12
8.8
70
Availability
7.4
14
8.4
62
8.2
12
8.5
66
8.8
12
8.6
68
Performance
8.6
12
8.5
65
Security
9.0
12
8.7
70
7.9
12
8.8
69
7.9
12
8.4
69
8.6
12
8.7
65
Support
8.9
12
8.7
66
8.2
12
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
79
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
80
Not enough data
8.7
78
Not enough data
8.7
80
Not enough data
8.7
78
Generative AI
Not enough data
7.5
51
Not enough data
7.8
51
Marketing Operations
Not enough data
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
Campaign Activity
Not enough data
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
Agentic AI - Marketing Analytics
Not enough data
8.8
16
Not enough data
9.6
16
Not enough data
8.3
16
Database
Not enough data
8.8
178
Not enough data
8.9
176
Not enough data
8.8
170
Integrations
Not enough data
8.4
139
Not enough data
8.6
136
Platform
Not enough data
8.9
153
Not enough data
8.9
168
Not enough data
8.6
136
Processing
Not enough data
9.3
170
Not enough data
9.1
164
Data Transformation
Not enough data
8.8
288
Not enough data
9.3
295
Connectivity
Not enough data
8.1
256
Not enough data
8.2
254
Not enough data
8.7
283
Not enough data
8.8
274
Operations
Not enough data
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
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 Parquet and Google Cloud BigQuery are categorized as Columnar Databases
Unique Categories
Apache Parquet has no unique categories
Google Cloud BigQuery is categorized as Big Data Integration Platforms, ETL Tools, Big Data Processing and Distribution, Big Data Analytics, Marketing Analytics, Predictive Analytics, Data Warehouse, and Data Clean Room
Reviews
Reviewers' Company Size
Apache Parquet
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
38.5%
Information Technology and Services
19.2%
Financial Services
7.7%
Education Management
7.7%
Hospital & Health Care
3.8%
Other
23.1%
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%
Alternatives
Discussions
Apache Parquet 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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