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Google Cloud Dataflow pros and cons

Vendor: Google

3.9 out of 5

10 reviews
90% willing to recommend

199 followers

Pros & Cons summary

Google Cloud Dataflow integrates seamlessly with the stack, offering pay-as-you-go service and a flexible programming environment. It is cost-effective and scalable, supporting streaming and data pipelines. Users appreciate its setup ease without constant server use. Strong support enhances the experience, but integration with Kafka and IT data flows, error logging, and authentication need improvement. Challenges with Google Cloud Composer require attention for optimized performance.

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Prominent pros & cons

PROS

Google Cloud Dataflow offers excellent integration and is straightforward to use within a complete stack.

The service is cost-effective, particularly when leveraging language flexibility for programming tasks.

It provides great scalability and allows programming in any language.

The service is known for its practical connectivity and is useful for streaming and data pipelines.

Its installation process is easy and the support team is highly regarded.

CONS

Google Cloud Dataflow needs better integration with Kafka topics to improve performance.

Error logging in Google Cloud Dataflow can be enhanced for quicker error resolution.

The deployment time for Google Cloud Dataflow should be minimized to increase efficiency.

Google Cloud Dataflow requires optimization in terms of cost for better value.

Authentication improvements are necessary for Google Cloud Dataflow.

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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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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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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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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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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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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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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Streaming Analytics

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Find out what your peers are saying about Google, Databricks, Apache and others in Streaming Analytics. Updated: December 2024.

824,067 professionals have used our research since 2012.

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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Associate Consultant (Data Engineer) at MediaAgility

Dec 19, 2023

Google Cloud Dataflow should include a little cost optimization.

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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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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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RK

Senior Software Engineer at Peristent Systems

Jan 9, 2024

They should do a market survey and then make improvements.

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Product Categories

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