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Confluent 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

Confluent
Ranking in Streaming Analytics
3rd
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
23
Ranking in other categories
No ranking in other categories
Google Cloud Dataflow
Ranking in Streaming Analytics
7th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
14
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2025, in the Streaming Analytics category, the mindshare of Confluent is 8.3%, down from 10.2% compared to the previous year. The mindshare of Google Cloud Dataflow is 6.0%, down from 7.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Gustavo-Barbosa Dos Santos - PeerSpot reviewer
Has good technical support services and a valuable feature for real-time data streaming
Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance. It helps us understand the various requirements of multiple customers and validates the information for different versions. We can automate the tasks using Confluent Kafka. Thus, it guarantees us the data quality and maintains the integrity of message contracts.
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

"It is also good for knowledge base management."
"The most valuable feature that we are using is the data replication between the data centers allowing us to configure a disaster recovery or software. However, is it's not mandatory to use and because most of the features that we use are from Apache Kafka, such as end-to-end encryption. Internally, we can develop our own kind of product or service from Apache Kafka."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"The benefit is escaping email communication. Sometimes people ignore emails or put them into spam, but with Confluence, everyone sees the same text at the same time."
"Our main goal is to validate whether we can build a scalable and cost-efficient way to replicate data from these various sources."
"The solution can handle a high volume of data because it works and scales well."
"We mostly use the solution's message queues and event-driven architecture."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"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."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"The support team is good and it's easy to use."
"The integration within Google Cloud Platform is very good."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"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 allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."
 

Cons

"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"Confluent's price needs improvement."
"They should remove Zookeeper because of security issues."
"Currently, in the early stages, I see a gap on the security side. If you are using the SaaS version, we would like to get a fuller, more secure solution that can be adopted right out of the box. Confluence could do a better job sharing best practices or a reusable pattern that others have used, especially for companies that can not afford to hire professional services from Confluent."
"There is no local support team in Saudi Arabia."
"The pricing model should include the ability to pick features and be charged for them only."
"The Schema Registry service could be improved. I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well."
"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 deployment time could also be reduced."
"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."
"The solution's setup process could be more accessible."
"The technical support has slight room for improvement."
"Occasionally, dealing with a huge volume of data causes failure due to array size."
"The authentication part of the product is an area of concern where improvements are required."
"Promoting the technology more broadly would help increase its adoption."
 

Pricing and Cost Advice

"Regarding pricing, I think Confluent is a premium product, but it's hard for me to say definitively if it's overly expensive. We're still trying to understand if the features and reduced maintenance complexity justify the cost, especially as we scale our platform use."
"Confluent is an expensive solution."
"It comes with a high cost."
"On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs."
"Confluence's pricing is quite reasonable, with a cost of around $10 per user that decreases as the number of users increases. Additionally, it's worth noting that for teams of up to 10 users, the solution is completely free."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"You have to pay additional for one or two features."
"Confluent is highly priced."
"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."
"Google Cloud is slightly cheaper than AWS."
"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."
"The tool is cheap."
"Google Cloud Dataflow is a cheap solution."
"The solution is not very expensive."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
15%
Manufacturing Company
6%
Retailer
5%
Financial Services Firm
17%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Confluent?
I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and to...
What is your experience regarding pricing and costs for Confluent?
They charge a lot for scaling, which makes it expensive.
What needs improvement with Confluent?
I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team. The lack of easy access to the Confluent support team is also a...
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 is your experience regarding pricing and costs for Google Cloud Dataflow?
Pricing is normal. It is part of a package received from Google, and they are not charging us too high.
What needs improvement with Google Cloud Dataflow?
I am not sure, as we built only one job, and it is running on a daily basis. Everything else is managed using BigQuery schedulers and Talend. However, occasionally, dealing with a huge volume of da...
 

Also Known As

No data available
Google Dataflow
 

Overview

 

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
Find out what your peers are saying about Confluent vs. Google Cloud Dataflow and other solutions. Updated: July 2025.
865,295 professionals have used our research since 2012.