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Confluent vs Spring Cloud Data Flow 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
Spring Cloud Data Flow
Ranking in Streaming Analytics
11th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Data Integration (20th)
 

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Confluent is 6.8%, down from 8.7% compared to the previous year. The mindshare of Spring Cloud Data Flow is 4.1%, down from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Confluent6.8%
Spring Cloud Data Flow4.1%
Other89.1%
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.
LN
Senior Software Engineer at QBE Regional Insurance
Provides ease of integration with other cloud platforms
Spring Cloud Data Flow is a useful product if I consider how there are different providers with whom my company had to deal, and most of them offer cloud-based products. I can't explain any crucial circumstances where the product's integration capabilities were helpful, but the aforementioned details explain the scenario for which I used the solution. I was only involved with the development of the product and not with the data pipeline configuration phase. The use of Spring Cloud Data Flow greatly impacted projects' time to market since our company's intention was to actually deploy and ensure that the payment platform integrated with it, which was an easy process. The product's user interface was very intuitive. The tool was deployed in multiple environments, but I am not sure about the production. From the time I started taking up the job in my current organization, I saw that we have deployed the tool in multiple environments wherein the number of users extensively used the product in the UAT environment, which is one of the most stable environments. There were 20 different methods to test the tool. I wouldn't be able to tell you the production details of the tool as I was more part of the production deployment, but I can say that it was deployed with the intent of making it available for 10,000 users. Those who plan to use the product should enjoy the flexibility of the solution. I rate the tool a nine out of ten.

Quotes from Members

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

Pros

"The biggest benefit of Confluent as a tool is that it is a distributed platform that provides more durability and stability."
"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."
"A person with a good IT background and HTML will not have any trouble with 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 tools."
"Confluence's greatest asset is its user-friendly interface, coupled with its remarkable ability to seamlessly integrate with a vast range of other solutions."
"The solution can handle a high volume of data because it works and scales well."
"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 client APIs are the most valuable feature."
"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"The most valuable feature is real-time streaming."
"The product is very user-friendly."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."
"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."
 

Cons

"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."
"There is no local support team in Saudi Arabia."
"In Confluent, there could be a few more VPN options."
"They should remove Zookeeper because of security issues."
"Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools."
"Confluent has fallen behind in being the tool of the industry. It's taking second place to things such as Word and SharePoint and other office tools that are more dynamic and flexible than Confluent."
"Confluent's price needs improvement."
"We continuously face issues, such as Kafka being down and slow responses from the support team."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"The solution's community support could be improved."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
"I would improve the dashboard features as they are not very user-friendly."
"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."
 

Pricing and Cost Advice

"It comes with a high cost."
"The solution is cheaper than other products."
"Confluent is highly priced."
"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."
"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 as we went for a three contract and it was very costly for us."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"You have to pay additional for one or two features."
"This is an open-source product that can be used free of charge."
"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."
"The solution provides value for money, and we are currently using its community edition."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
11%
Retailer
9%
Manufacturing Company
7%
Financial Services Firm
20%
Computer Software Company
13%
Retailer
9%
Government
5%
 

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 Enterprise1
Large Enterprise5
 

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 needs improvement with Spring Cloud Data Flow?
There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...
What is your primary use case for Spring Cloud Data Flow?
We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...
What advice do you have for others considering Spring Cloud Data Flow?
I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...
 

Overview

 

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
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Find out what your peers are saying about Confluent vs. Spring Cloud Data Flow and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.