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Apache Flink vs Confluent 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

Apache Flink
Ranking in Streaming Analytics
5th
Average Rating
7.8
Reviews Sentiment
6.9
Number of Reviews
18
Ranking in other categories
No ranking in other categories
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
 

Mindshare comparison

As of July 2025, in the Streaming Analytics category, the mindshare of Apache Flink is 13.9%, up from 9.7% compared to the previous year. The mindshare of Confluent is 8.3%, down from 10.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Aswini Atibudhi - PeerSpot reviewer
Enables robust real-time data processing but documentation needs refinement
Apache Flink is very powerful, but it can be challenging for beginners because it requires prior experience with similar tools and technologies, such as Kafka and batch processing. It's essential to have a clear foundation; hence, it can be tough for beginners. However, once they grasp the concepts and have examples or references, it becomes easier. Intermediate users who are integrating with Kafka or other sources may find it smoother. After setting up and understanding the concepts, it becomes quite stable and scalable, allowing for customization of jobs. Every ( /products/every-reviews ) software, including Apache Flink, has room for improvement as it evolves. One key area for enhancement is user-friendliness and the developer experience; improving documentation and API specifications is essential, as they can currently be verbose and complex. Debugging ( /categories/debugging ) and local testing pose challenges for newcomers, particularly when learning about concepts such as time semantics and state handling. Although the APIs exist, they aren't intuitive enough. We also need to simplify operational procedures, such as developing tools and tuning Flink clusters, as these processes can be quite complex. Additionally, implementing one-click rollback for failures and improving state management during dynamic scaling while retaining the last states is vital, as the current large states pose scaling challenges.
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.

Quotes from Members

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

Pros

"The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."
"What I appreciate best about Apache Flink is that it's open source and geared towards a distributed stream processing framework."
"This is truly a real-time solution."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"The ease of usage, even for complex tasks, stands out."
"Apache Flink is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"The setup was not too difficult."
"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 monitoring module is impressive."
"Confluence's greatest asset is its user-friendly interface, coupled with its remarkable ability to seamlessly integrate with a vast range of other solutions."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future."
"One of the best features of Confluent is that it's very easy to search and have a live status with Jira."
"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."
 

Cons

"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"Apache Flink should improve its data capability and data migration."
"There are more libraries that are missing and also maybe more capabilities for machine learning."
"The solution could be more user-friendly."
"Apache should provide more examples and sample code related to streaming to help me better adapt and utilize the tool."
"Apache Flink's documentation should be available in more languages."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"One way to improve Flink would be to enhance integration between different ecosystems. For example, there could be more integration with other big data vendors and platforms similar in scope to how Apache Flink works with Cloudera. Apache Flink is a part of the same ecosystem as Cloudera, and for batch processing it's actually very useful but for real-time processing there could be more development with regards to the big data capabilities amongst the various ecosystems out there."
"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."
"The pricing model should include the ability to pick features and be charged for them only."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"Confluent's price needs improvement."
"There is a limitation when it comes to seamlessly importing Microsoft documents into Confluent pages, which can be inconvenient for users who frequently work with Microsoft Office tools and need to transition their content to Confluent."
"It could have more integration with different platforms."
"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."
"We continuously face issues, such as Kafka being down and slow responses from the support team."
 

Pricing and Cost Advice

"It's an open source."
"Apache Flink is open source so we pay no licensing for the use of the software."
"This is an open-source platform that can be used free of charge."
"It's an open-source solution."
"The solution is open-source, which is 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."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"It comes with a high cost."
"The solution is cheaper than other products."
"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."
"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."
"Confluent is an expensive solution."
"Confluent is highly priced."
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Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
14%
Manufacturing Company
7%
Retailer
6%
Financial Services Firm
18%
Computer Software Company
16%
Manufacturing Company
6%
Insurance Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Flink?
The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. ...
What is your experience regarding pricing and costs for Apache Flink?
The solution is expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.
What needs improvement with Apache Flink?
Apache should provide more examples and sample code related to streaming to help me better adapt and utilize the tool. There is a need for increased awareness and education, especially around best ...
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...
 

Comparisons

 

Also Known As

Flink
No data available
 

Overview

 

Sample Customers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
Find out what your peers are saying about Apache Flink vs. Confluent and other solutions. Updated: July 2025.
862,624 professionals have used our research since 2012.