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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
4th
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
7.8
Reviews Sentiment
7.3
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of March 2025, in the Streaming Analytics category, the mindshare of Confluent is 8.6%, down from 11.5% compared to the previous year. The mindshare of Google Cloud Dataflow is 7.4%, up from 6.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Yantao Zhao - PeerSpot reviewer
Great tool for sharing knowledge, internal communication and allows for real-time collaboration on pages
Confluence is easy to use and modify. However, sometimes there are too many pages. We have to reorganize the folder or parent account. Since everyone can create a page, the same knowledge might be created in multiple places by different people. This leads to redundancy and makes it difficult to find information. It's not centralized. So it could be more user-friendly and centralized. A way to reduce redundancy would be helpful. It's very easy to use, so everyone can create knowledge. But it would be good to synchronize and organize that information a bit better. Another improvement would be in Confluence search. You can search for keywords, but it's not like AI, not even ChatGPT or OpenAI. It would be nice to get more relevant or organized answers. If you're outside the company, you just get some titles containing the keyword you input. But if Confluence were like a database, you could input something and get a well-organized search offering from multiple pages.
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

"With Confluent Cloud we no longer need to handle the infrastructure and the plumbing, which is a concern for Confluent. The other advantage is that all portfolios have access to the data that is being shared."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."
"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 tools."
"The client APIs are the most valuable feature."
"It is also good for knowledge base management."
"Their tech support is amazing; they are very good, both on and off-site."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"I would rate the overall solution a ten out of ten."
"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 service is relatively cheap compared to other batch-processing engines."
"The best feature of Google Cloud Dataflow is its practical connectedness."
"It is a scalable solution."
"The support team is good and it's easy to use."
 

Cons

"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"The formatting aspect within the page can be improved and more powerful."
"It requires some application specific connectors which are lacking. This needs to be added."
"I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"There is no local support team in Saudi Arabia."
"there is room for improvement in the visualization."
"It could have more integration with different platforms."
"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."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"The deployment time could also be reduced."
"Google Cloud Dataflow should include a little cost optimization."
"The technical support has slight room for improvement."
"Promoting the technology more broadly would help increase its adoption."
"The authentication part of the product is an area of concern where improvements are required."
"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."
 

Pricing and Cost Advice

"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."
"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."
"You have to pay additional for one or two features."
"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 has a yearly license, which is a bit high because it's on a per-user basis."
"Confluent is an expensive solution."
"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."
"It comes with a high cost."
"The tool is cheap."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"The solution is cost-effective."
"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 solution is not very expensive."
"Google Cloud Dataflow is a cheap solution."
"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
Financial Services Firm
19%
Computer Software Company
16%
Manufacturing Company
7%
Insurance Company
5%
Financial Services Firm
17%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
11%
 

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?
Google Cloud Dataflow costs are primarily driven by compute resources (worker type and count) and data volume. However, other factors like pipeline complexity also contribute significantly to the t...
What needs improvement with Google Cloud Dataflow?
Apache Beam represents a powerful data processing solution that deserves wider recognition in the broader tech community. This technology offers remarkable capabilities for handling data at scale, ...
 

Comparisons

 

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: March 2025.
842,194 professionals have used our research since 2012.