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Google Cloud Dataflow pros and cons

Vendor: Google

4.0 out of 5

14 reviews
93% willing to recommend

Pros & Cons summary

Google Cloud Dataflow integrates well with Google Cloud Platform, offering scalability ideal for streaming and data pipelines. It supports any programming language, improving flexibility for users. The pay-as-you-go model is cost-effective, supported by a reliable team. However, improvements are needed in Kafka integration, error logging, authentication, cost optimization, and schema design in NoSQL storage for enhanced scalability.

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Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Google Cloud Dataflow offers excellent scalability and connectivity, making it highly effective for streaming and data pipelines.

The integration within Google Cloud is seamless, simplifying processes for those utilizing the complete stack.

Google Cloud Dataflow is very flexible for programmers, allowing coding in any language, which enhances usability.

Its cost-effectiveness is enhanced by a pay-as-you-go service, making it relatively inexpensive compared to other engines.

Support from Google's team is excellent, resolving issues efficiently, especially with large data handling.

CONS

Google Cloud Dataflow can improve integration with Kafka topics and IT data flow services.

There is a need for better error logging and debugging capabilities.

The deployment time and setup process could be more efficient.

Improvements in authentication and cost optimization are necessary.

Handling large data volumes occasionally leads to failures due to array size limitations.

Google Cloud Dataflow Pros review quotes

Head of Data and Analytics at a tech services company with 201-500 employees

Jun 28, 2022

The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use.

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Darasimi Ajewole

Software Engineer at Formplus

Nov 26, 2022

The service is relatively cheap compared to other batch-processing engines.

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reviewer2086836

System Architect at a financial services firm with 5,001-10,000 employees

Feb 24, 2023

The solution allows us to program in any language we desire.

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Google Cloud Dataflow

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Learn what your peers think about Google Cloud Dataflow. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.

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ChatGPT Specialist at Stealth Mode

May 23, 2023

I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service.

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Bunyamin Altınsoy

Cloud Solution Architect at NGC | Google Cloud Partner EMEA

Jun 27, 2023

The best feature of Google Cloud Dataflow is its practical connectedness.

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Amitabha Chakraborty

Data Analyst Manager at a retailer with 10,001+ employees

Jun 30, 2023

It is a scalable solution.

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Principal Solution Architect at Tech Mahindra Limited

Oct 11, 2023

Google Cloud Dataflow is useful for streaming and data pipelines.

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Associate Consultant (Data Engineer) at MediaAgility

Dec 19, 2023

The most valuable features of Google Cloud Dataflow are scalability and connectivity.

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RK

Senior Software Engineer at Peristent Systems

Jan 9, 2024

The support team is good and it's easy to use.

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Satellite System Engineer at NARSS

Feb 14, 2024

The product's installation process is easy...The tool's maintenance part is somewhat easy.

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Google Cloud Dataflow Cons review quotes

Head of Data and Analytics at a tech services company with 201-500 employees

Jun 28, 2022

Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job.

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Darasimi Ajewole

Software Engineer at Formplus

Nov 26, 2022

The deployment time could also be reduced.

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reviewer2086836

System Architect at a financial services firm with 5,001-10,000 employees

Feb 24, 2023

The technical support has slight room for improvement.

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Google Cloud Dataflow

Free Report: Google Cloud Dataflow Reviews and More

Learn what your peers think about Google Cloud Dataflow. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.

881,082 professionals have used our research since 2012.

ChatGPT Specialist at Stealth Mode

May 23, 2023

When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs.

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Bunyamin Altınsoy

Cloud Solution Architect at NGC | Google Cloud Partner EMEA

Jun 27, 2023

I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool.

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Amitabha Chakraborty

Data Analyst Manager at a retailer with 10,001+ employees

Jun 30, 2023

The solution's setup process could be more accessible.

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Principal Solution Architect at Tech Mahindra Limited

Oct 11, 2023

There are certain challenges regarding the Google Cloud Composer which can be improved.

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Associate Consultant (Data Engineer) at MediaAgility

Dec 19, 2023

Google Cloud Dataflow should include a little cost optimization.

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RK

Senior Software Engineer at Peristent Systems

Jan 9, 2024

They should do a market survey and then make improvements.

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Satellite System Engineer at NARSS

Feb 14, 2024

The authentication part of the product is an area of concern where improvements are required.

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Show 3 more reviews (out of 13)

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Streaming Analytics

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