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Compare Apache Kafka and Google Cloud Dataflow 
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At a Glance
Market Segments
Enterprise (47.5% of reviews)
Small-Business (33.3% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Apache Kafka
Star Rating
(125)4.5 out of 5
Market Segments
Enterprise (47.5% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Apache KafkaGoogle Cloud Dataflow
Star Rating
(44)4.2 out of 5
Market Segments
Small-Business (33.3% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Google Cloud DataflowSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Google Cloud Dataflow excels in data processing capabilities, scoring a remarkable 9.7, while Apache Kafka, although strong, scores slightly lower at 8.9. Reviewers mention that Dataflow's ability to handle batch and stream processing seamlessly is a significant advantage for real-time analytics.
- Reviewers mention that Google Cloud Dataflow offers superior integration with various data sources, achieving a score of 9.5 compared to Apache Kafka's 8.7. Users on G2 highlight Dataflow's ease of connecting with Google services and other cloud platforms as a key feature that enhances its usability.
- G2 users report that Apache Kafka shines in asynchronous messaging, scoring 9.0, which is crucial for applications requiring high throughput and low latency. Users say that Kafka's robust messaging system is particularly beneficial for event-driven architectures.
- Users say that Google Cloud Dataflow's real-time processing capabilities are impressive, with a score of 9.5, while Apache Kafka follows closely with 9.1. Reviewers mention that Dataflow's ability to automatically scale resources based on workload is a game-changer for handling variable data loads.
- Reviewers mention that while both platforms have strong support, Google Cloud Dataflow scores higher in quality of support at 8.3 compared to Kafka's 7.7. Users report that Dataflow's support team is responsive and helpful, which is crucial for businesses relying on timely assistance.
- Users on G2 report that Google Cloud Dataflow's ease of use is rated at 7.9, which is lower than Apache Kafka's 8.6. Reviewers mention that Kafka's straightforward setup process and user-friendly interface make it a preferred choice for teams looking to implement a messaging system quickly.
Pricing
Entry-Level Pricing
Apache Kafka
No pricing availableGoogle Cloud Dataflow
No pricing availableFree Trial
Apache Kafka
No trial information availableGoogle Cloud Dataflow
No trial information availableRatings
Meets Requirements
8.9
90
9.0
24
Ease of Use
8.6
90
8.1
24
Ease of Setup
8.0
28
7.9
7
Ease of Admin
7.8
24
8.0
5
Quality of Support
7.8
81
8.3
21
Has the product been a good partner in doing business?
8.3
20
9.0
5
Product Direction (% positive)
8.8
87
9.0
23
Features by Category
Data
8.8
33
9.8
7
8.7
35
9.6
8
8.9
35
9.3
7
9.0
35
9.6
8
Analytics
8.3
31
8.3
5
Functionality
8.9
52
Not enough data
8.5
49
Not enough data
8.3
45
Not enough data
8.1
49
Not enough data
Integration
8.8
51
Not enough data
8.4
47
Not enough data
8.1
46
Not enough data
Management
8.2
42
Not enough data
8.0
42
Not enough data
8.3
43
Not enough data
Agentic AI - Message Queue (MQ)
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Database
Not enough data
8.3
11
Not enough data
8.9
11
Not enough data
8.5
10
Integrations
Not enough data
6.9
7
Not enough data
6.9
8
Platform
Not enough data
8.8
11
Not enough data
8.6
12
Not enough data
6.9
8
Processing
Not enough data
8.9
12
Not enough data
9.2
10
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 Kafka and Google Cloud Dataflow are categorized as Event Stream Processing
Unique Categories
Apache Kafka is categorized as Message Queue (MQ) and Stream Analytics
Google Cloud Dataflow is categorized as Big Data Processing and Distribution
Reviews
Reviewers' Company Size
Apache Kafka
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Google Cloud Dataflow
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
25.0%
Information Technology and Services
18.3%
Financial Services
8.3%
Banking
5.8%
Retail
4.2%
Other
38.3%
Computer Software
11.9%
Internet
7.1%
Entertainment
7.1%
Management Consulting
4.8%
Insurance
4.8%
Other
64.3%
Alternatives
Discussions
What is Apache Kafka used for?
2 Comments
RS
I am using Apache Kafka for event Processing. We use it to capture the new events generated by our application in our database. Currently, Kafka streams is...Read more
What is the maximum limit of the number of partitions in a Kafka topic?
1 Comment
CT
The answer is closely related to the version of the Kafka broker that you are running. A reasonably up to date cluster can hold up to 4,000 partitions per...Read more
What is Apache Kafka used for?
1 Comment
DV
It used this Mnemonic to remember what kafka is and what it is used for -
S - Stream Data in Real-Time:
Handles and processes live data (e.g., Uber car...Read more
Google Cloud Dataflow has no discussions with answers
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