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Cloudera DataFlow vs Google Cloud Dataflow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Cloudera DataFlow
Ranking in Streaming Analytics
14th
Average Rating
7.2
Reviews Sentiment
6.3
Number of Reviews
4
Ranking in other categories
No ranking in other categories
Google Cloud Dataflow
Ranking in Streaming Analytics
8th
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
11
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2025, in the Streaming Analytics category, the mindshare of Cloudera DataFlow is 1.1%, down from 1.5% compared to the previous year. The mindshare of Google Cloud Dataflow is 7.7%, up from 6.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Júlio César Gomes Fonseca - PeerSpot reviewer
A stable solution that helps develop quality modules but needs to improve its programming language
The initial setup was not so difficult. The deployment took so long, at least one or two years, because the team has a project that aims to be exceptional in the future. It's good to say because the company is very good. It's a self-confirmation technical integration company. We have numerous reasons why reducing staff workload is beneficial. However, it is important to note that this does not directly apply to the application used. They will only do the service.
Jana Polianskaja - PeerSpot reviewer
Build Scalable Data Pipelines with Apache Beam and Google Cloud Dataflow
As a data engineer, I find several features of Google Cloud Dataflow particularly valuable. The ability to test solutions locally using Direct Runner is crucial for development, allowing me to validate pipelines without incurring the costs of full Dataflow jobs. The unified programming model for both batch and streaming processing is exceptional - requiring only minor code adjustments to optimize for either mode. This flexibility extends to language support, with robust implementations in both Java and Python, allowing teams to leverage their existing expertise. The platform's comprehensive monitoring capabilities are another standout feature. The intuitive interface, Grafana integration, and extensive service connectivity make troubleshooting and performance tracking highly efficient. Furthermore, seamless integration with Google Cloud Composer (managed Airflow) enables sophisticated orchestration of data pipelines.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"DataFlow's performance is okay."
"This solution is very scalable and robust."
"The initial setup was not so difficult"
"The most effective features are data management and analytics."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"I would rate the overall solution a ten out of ten."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"The support team is good and it's easy to use."
"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."
"It is a scalable solution."
"The solution allows us to program in any language we desire."
"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."
 

Cons

"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."
"It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."
"The authentication part of the product is an area of concern where improvements are required."
"They should do a market survey and then make improvements."
"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."
"The solution's setup process could be more accessible."
"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."
"Google Cloud Dataflow should include a little cost optimization."
"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."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
 

Pricing and Cost Advice

"DataFlow isn't expensive, but its value for money isn't great."
"The solution is cost-effective."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"Google Cloud is slightly cheaper than AWS."
"The solution is not very expensive."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."
"Google Cloud Dataflow is a cheap solution."
"The tool is cheap."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
16%
University
15%
Manufacturing Company
6%
Financial Services Firm
17%
Retailer
12%
Manufacturing Company
12%
Computer Software Company
12%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Cloudera DataFlow?
The most effective features are data management and analytics.
What is your primary use case for Cloudera DataFlow?
We use Cloudera DataFlow for stream analytics.
What do you like most about Google Cloud Dataflow?
The product's installation process is easy...The tool's maintenance part is somewhat easy.
What needs improvement with Google Cloud Dataflow?
The authentication part of the product is an area of concern where improvements are required. For some common users, the solution's authentication part is difficult to use. The scalability of the p...
 

Also Known As

CDF, Hortonworks DataFlow, HDF
Google Dataflow
 

Overview

 

Sample Customers

Clearsense
Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
Find out what your peers are saying about Cloudera DataFlow vs. Google Cloud Dataflow and other solutions. Updated: January 2025.
837,501 professionals have used our research since 2012.