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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
5th
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
25
Ranking in other categories
No ranking in other categories
Google Cloud Dataflow
Ranking in Streaming Analytics
9th
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 February 2026, in the Streaming Analytics category, the mindshare of Confluent is 6.8%, down from 8.5% compared to the previous year. The mindshare of Google Cloud Dataflow is 4.2%, down from 7.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Confluent6.8%
Google Cloud Dataflow4.2%
Other89.0%
Streaming Analytics
 

Featured Reviews

PavanManepalli - PeerSpot reviewer
AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo
Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing
I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.
Jana Polianskaja - PeerSpot reviewer
Data Engineer at Accenture
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

"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"One of the best features of Confluent is that it's very easy to search and have a live status with Jira."
"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"The design of the product is extremely well built and it is highly configurable."
"It is also good for knowledge base management."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"The features I find most useful in Confluent are the Multi-Region Cluster, MRC, and the Cluster Linking for replication."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The solution allows us to program in any language we desire."
"It allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The integration within Google Cloud Platform is very good."
"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."
"The support team is good and it's easy to use."
"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

"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."
"Confluent has a good monitoring tool, but it's not customizable."
"I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"They should remove Zookeeper because of security issues."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"Confluent's price needs improvement."
"It requires some application specific connectors which are lacking. This needs to be added."
"The authentication part of the product is an area of concern where improvements are required."
"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."
"Occasionally, dealing with a huge volume of data causes failure due to array size."
"The solution's setup process could be more accessible."
"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."
"The technical support has slight room for improvement."
"Google Cloud Dataflow should include a little cost optimization."
"Promoting the technology more broadly would help increase its adoption."
 

Pricing and Cost Advice

"It comes with a high cost."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"You have to pay additional for one or two features."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"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."
"The solution is cheaper than other products."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"The pricing model of Confluent could improve because if you have a classic use case where you're going to use all the features there is no plan to reduce the features. You should be able to pick and choose basic services at a reduced price. The pricing was high for our needs. We should not have to pay for features we do not use."
"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."
"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."
"The tool is cheap."
"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 solution is not very expensive."
"Google Cloud is slightly cheaper than AWS."
"Google Cloud Dataflow is a cheap solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
11%
Retailer
9%
Manufacturing Company
6%
Financial Services Firm
18%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise4
Large Enterprise16
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise10
 

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 recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about ...
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?
It can be improved in several ways. The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability. Implementing AI-based suggest...
 

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: December 2025.
881,707 professionals have used our research since 2012.