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Compare Amazon Kinesis Data Firehose and Google Cloud BigQuery 
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At a Glance
Market Segments
Mid-Market (55.0% of reviews)
Enterprise (38.1% of reviews)
Entry-Level Pricing
No pricing available
Free
Amazon Kinesis Data Firehose
Star Rating
(24)4.2 out of 5
Market Segments
Mid-Market (55.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Amazon Kinesis Data FirehoseGoogle 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 plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Google Cloud BigQuery excels in data querying capabilities, with a score of 9.3, allowing for complex queries to be executed efficiently. In contrast, Amazon Kinesis Data Firehose has a lower score of 8.8 in this area, which may affect users needing advanced querying features.
- Reviewers mention that Google Cloud BigQuery's built-in data analytics feature scores 8.6, providing robust analytics tools directly within the platform. Meanwhile, Amazon Kinesis Data Firehose lacks this integrated analytics capability, which could lead to additional costs for users needing separate analytics solutions.
- G2 users highlight that Google Cloud BigQuery offers superior data quality management with a score of 8.8, ensuring that users can maintain high standards for their data. On the other hand, Amazon Kinesis Data Firehose scores slightly lower at 8.3, which may raise concerns for users prioritizing data integrity.
- Users on G2 report that Google Cloud BigQuery's data integration capabilities are rated at 9.0, making it easier to connect with various data sources. In contrast, Amazon Kinesis Data Firehose scores 7.5, indicating potential challenges for users looking to integrate diverse data streams seamlessly.
- Reviewers mention that Google Cloud BigQuery's performance and reliability score is 9.1, reflecting its strong uptime and processing capabilities. Conversely, Amazon Kinesis Data Firehose, with a score of 8.6, may not meet the same level of reliability, which could be a critical factor for users with high availability requirements.
- Users say that Google Cloud BigQuery's automation features score 8.9, allowing for efficient data processing workflows. In comparison, Amazon Kinesis Data Firehose scores 9.3 in automation, indicating that it may offer more advanced automation options, which could be beneficial for users looking to streamline their data handling processes.
Pricing
Entry-Level Pricing
Amazon Kinesis Data Firehose
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
Amazon Kinesis Data Firehose
No trial information availableGoogle Cloud BigQuery
Free Trial is available
Ratings
Meets Requirements
8.5
17
8.8
612
Ease of Use
8.3
17
8.7
626
Ease of Setup
8.6
7
8.8
401
Ease of Admin
9.2
6
8.5
224
Quality of Support
8.2
17
8.4
564
Has the product been a good partner in doing business?
8.9
6
8.7
217
Product Direction (% positive)
9.3
17
9.2
600
Features by Category
Data
8.3
8
Not enough data
7.5
8
Not enough data
7.7
5
Not enough data
8.1
8
Not enough data
Analytics
7.7
8
Not enough data
Management
8.2
10
8.6
123
8.3
9
8.3
121
Functionality
8.3
10
9.0
121
8.2
10
9.1
124
8.8
10
9.0
124
9.3
10
8.9
123
9.3
10
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
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
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
Amazon Kinesis Data Firehose and Google Cloud BigQuery are categorized as ETL Tools
Unique Categories
Amazon Kinesis Data Firehose is categorized as Stream Analytics and Event Stream Processing
Google Cloud BigQuery is categorized as Columnar Databases, Big Data Integration Platforms, Big Data Processing and Distribution, Big Data Analytics, Marketing Analytics, Predictive Analytics, Data Warehouse, and Data Clean Room
Reviews
Reviewers' Company Size
Amazon Kinesis Data Firehose
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
20.0%
Information Technology and Services
15.0%
Consumer Services
10.0%
Real Estate
5.0%
Online Media
5.0%
Other
45.0%
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
Amazon Kinesis Data Firehose 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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