Apache Flink vs Confluent comparison

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Apache Flink

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Executive SummaryUpdated on Dec 17, 2024

Confluent and Apache Flink compete in the data streaming and processing domain. Confluent generally takes the upper hand in interconnectivity and integrated solutions, whereas Apache Flink excels in robust processing features, scalability, and advanced stream analytics.

Features: Confluent leverages its comprehensive Kafka integration, offering seamless data streams, scalability, and a variety of connectors. Its user-friendly interface and integrated platform make it a leading choice for enterprises seeking efficient stream processing. Apache Flink stands out with its advanced real-time data processing features, low-latency operations, and stateful event processing capabilities, ideal for sophisticated data computations. The checkpointing and savepointing features in Flink enable effective state management, allowing recovery and continuity in case of failures.

Room for Improvement: Confluent could benefit from enhanced documentation and reducing initial setup costs to lower entry barriers. While its integrations are comprehensive, further expansion of connector support would be advantageous. For Apache Flink, improving user support and providing more tailored deployment assistance would address the needs of less technically proficient users. Simplifying its setup process and enhancing community engagement for broader technical support could also be beneficial.

Ease of Deployment and Customer Service: Confluent offers straightforward deployment, particularly within Kafka environments, supported by a solid customer service model that enhances operational efficiency. Apache Flink provides flexible deployment options, accommodating bespoke solutions with the requirement of technical proficiency for optimal setup. Its adaptability allows for advanced customization but demands in-depth technical knowledge for seamless implementation.

Pricing and ROI: Confluent's initial setup costs are higher due to its integrated platform, but it often justifies this with strong ROI through enhanced efficiency in Kafka-based implementations. Apache Flink offers a cost-effective open-source model, appealing to organizations capable of leveraging its advanced functionalities for complex real-time analytics, providing financial flexibility and substantial ROI.

To learn more, read our detailed Apache Flink vs. Confluent Report (Updated: June 2026).

Apache Flink vs. Confluent

June 2026

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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

4th

Average Rating

7.8

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Confluent

Ranking in Streaming Analytics

7th

Average Rating

8.2

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Streaming Analytics category, the mindshare of Apache Flink is 7.5%, down from 14.4% compared to the previous year. The mindshare of Confluent is 6.4%, down from 8.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Flink	7.5%
Confluent	6.4%
Other	86.1%

Streaming Analytics

Featured Reviews

Sanjay Srivastava

Software Architect at IBM

Streaming workflows have improved data integration and support real-time pipelines across platforms

We are not using Apache Flink in its advanced window capabilities. We are using the Apache Flink job in Apache SeaTunnel, meaning we can write the code inside Apache SeaTunnel. Currently, we are moving; both solutions are there. We are doing it on-premises with the help of Kubernetes and OpenShift. The main reason why Apache Flink is better is that it has more functions, and being open source with easy code in Apache SeaTunnel helps us achieve that. Cost is a major issue. I would rate the stability of the product as an eight. For Apache Flink, the final point can be rated an eight. I can recommend Apache Flink to other users for streaming support, and I am recommending it. I would rate this review an eight overall.

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PavanManepalli

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.

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Quotes from Members

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

Pros

"The end-to-end latency was drastically reduced, and our capability of handling high throughput has increased by using Flink."

"The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."

"We are very happy with the product, and we have been able to achieve all of the use cases that we are expected to deliver for our customers."

"Among all of this, if I would talk about streaming, Apache Flink wins hands down, but there are other products like Apache Pulsar which I have no idea."

"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."

"Easy to deploy and manage."

"We value this solution's intricate system because it comes with a state inside the mechanism and product, allowing us to process batch data, stream to real-time and build pipelines, and we do not need to process data from the beginning when we pause as we can continue from the same point where we stopped, helping us save time as 95% of our pipelines will now be on Amazon and we'll save money by saving time."

"The ease of usage, even for complex tasks, stands out."

More Apache Flink pros

"The features I find most useful in Confluent are the Multi-Region Cluster, MRC, and the Cluster Linking for replication."

"The monitoring module is impressive."

"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."

"The biggest benefit of Confluent as a tool is that it is a distributed platform that provides more durability and stability."

"One of the best features of Confluent is that it's very easy to search and have a live status with Jira."

"We primarily use Confluent for service desk and task management, and it is also good for knowledge base management."

"Overall, it's a great company and they have excellent software."

"We mostly use the solution's message queues and event-driven architecture."

More Confluent pros

Cons

"Flink has become a lot more stable but the machine learning library is still not very flexible."

"Failure is another area where it is a bit rigid or not that flexible."

"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."

"There is room for improvement in the initial setup process."

"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."

"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."

"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."

"I am using the Python API and I have found the solution to be underdeveloped compared to others. There needs to be better integration with notebooks to allow for more practical development."

More Apache Flink cons

"It could have more themes. The themes in the version I'm using are very limited; they offer two to three themes."

"One area we've identified that could be improved is the governance and access control to the Kafka topics. We've found some limitations, like a threshold of 10,000 rules per cluster, that make it challenging to manage access at scale if we have many different data sources."

"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 formatting aspect within the page can be improved and more powerful."

"The solution could have an extra plugin or upgrading feature. In addition, it could have more integration with different platforms and be more compatible."

"The beginner who doesn't know how to work on HTML will struggle as when you create spaces in the Confluent, if you want to have some meeting notes or anything else, you need to know HTML and which HTML tags to include."

"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."

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."

More Confluent cons

Pricing and Cost Advice

"Apache Flink is open source so we pay no licensing for the use of the software."

"The solution is open-source, which is free."

"It's an open-source solution."

"This is an open-source platform that can be used free of charge."

"It's an open source."

"You have to pay additional for one or two features."

"The solution is cheaper than other products."

"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 highly priced."

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."

"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 has a yearly license, which is a bit high because it's on a per-user basis."

"Confluent is an expensive solution as we went for a three contract and it was very costly for us."

More Confluent pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Retailer

13%

Computer Software Company

Comms Service Provider

Financial Services Firm

15%

Retailer

12%

Computer Software Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	3
Large Enterprise	12

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	4
Large Enterprise	17

Questions from the Community

What needs improvement with Apache Flink?

Apache could improve Apache Flink by providing more functionality, as they need to fully support data integration. The connectors are still very few for Apache Flink. There is a lack of functionali...

What is your primary use case for Apache Flink?

I am working with Apache Flink, which is the tool we use for data integration. Apache Flink is for data, and we are working on the data integration project, not big data, using Apache Flink and Apa...

What advice do you have for others considering Apache Flink?

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?

What is your primary use case for Confluent?

The main use cases for Confluent are log aggregation and streaming. I'm familiar with Confluent stream processing with KSQL. KSQL helps in terms of data analytics strategies because if we are the d...

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Product Reports

Download Apache Flink product report

Apache Flink

August 2026

Download Confluent product report

August 2026

Also Known As

Flink

No data available

Overview

Apache Flink is a powerful open-source framework for stateful computations over data streams, designed for both real-time and batch processing. It efficiently handles massive volumes of data with low-latency responses, offering versatility for complex event processing scenarios.

Apache Flink excels in processing high-throughput data streams, enabling seamless state management across distributed applications. Users appreciate its robust features like stateful transformations and checkpointing, simplifying deployment in diverse environments. Though powerful, it poses challenges for beginners due to its complexity and limited documentation, requiring some prior experience to master. Its flexible integration with systems like Kafka and support for Kubernetes on AWS makes it suitable for demanding environments where quick, real-time analysis is essential.

What are the key features of Apache Flink?

Stateful Transformations: Allows complex stateful operations on data streams with precise handling.
Low Latency: Ensures real-time data processing with minimal delays.
Checkpointing: Provides efficient and reliable checkpointing for fault tolerance.
Kafka Integration: Easy integration with Kafka for seamless data ingestion and processing.
API Support: Provides robust APIs for diverse data processing needs.
Flexible Deployment: Offers options for deploying on-premise or in cloud environments.

What benefits should users look for?

Versatility: Supports both batch and stream processing in a unified model.
Community Support: Backed by an active community that continuously enhances its features.
Ease of Use: Simplifies the coding process compared to similar frameworks like Apache Storm.
Real-Time Analytics: Facilitates immediate insights and data-driven decision-making.

Organizations leverage Apache Flink primarily for real-time data processing in sectors such as retail, transportation, and telecommunications. By deploying on AWS with Kubernetes, companies can utilize it for data cleaning, generating customer insights, and providing swift real-time updates. It effectively manages millions of events per second, serving use cases like cab aggregations, map-making, and outlier detection in telecom networks, enabling seamless integration of streaming data with existing pipelines.

Apache

Confluent offers scalable, open-source flexibility and seamless data replication, supported by strong cloud integration. Key features like Kafka Connect and real-time processing make it valuable for data streaming projects while ensuring high availability with a Multi-Region Cluster.

Confluent is a robust data streaming platform that enables efficient management and integration of real-time data pipelines. Its message-driven architecture and fault tolerance provide reliability, while a user-friendly dashboard and connectors support diverse data sources. Cloud integration reduces costs, and extensive documentation, plugins, and monitoring capabilities enhance collaboration and revision management. Despite some areas needing improvement, including security in the SaaS version and integration flexibility, Confluent remains a staple in industries requiring vast data processing and task automation.

What are Confluent's key features?

Scalability: Handles large volumes of data, ensuring continuous performance.
Kafka Connect: Enables seamless data integration across multiple systems.
Real-time Processing: Facilitates instant data insights for rapid decision-making.
Multi-Region Cluster: Maintains data availability across different geographical locations.
Cloud Integration: Reduces operational costs and enhances deployment flexibility.
User Dashboard: Simplifies management with an intuitive interface.

What benefits and ROI should users consider in reviews?

Cost-Efficiency: Improved processes reduce operational expenses.
Data Reliability: Ensures consistent and accurate data handling.
Increased Collaboration: Boosts team efficiency with comprehensive documentation and management tools.
Scalability: Supports business growth without compromising performance.
Integration Flexibility: Seamlessly connects with diverse data sources and systems.

Confluent is commonly implemented in finance, insurance, and software industries for applications like fraud detection, ETL tasks, and enterprise communication. It supports real-time data processing, project management, and task automation, often integrating with project management tools like Jira, providing valuable solutions for business processes.

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