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Apache Kafka on Confluent Cloud vs Kubecost comparison

Confluent and Kubecost are both solutions in the AWS Marketplace category. Confluent is ranked #2 with an average rating of 8.3, while Kubecost is ranked #24 with an average rating of 9.3. Confluent holds a 0.8% mindshare in AWSM, compared to Kubecost’s 0.2% mindshare. Additionally, 100% of Confluent users are willing to recommend the solution, compared to 100% of Kubecost users who would recommend it.
Apache Kafka on Confluent C...
Read 11 Apache Kafka on Confluent Cloud reviews
  • 530 Views
  • 422 Comparison Views
100% willing to recommend
Kubecost
Read 3 Kubecost reviews
  • 165 Views
  • 92 Comparison Views
100% willing to recommend
 

Comparison Buyer's Guide

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Executive Summary
We performed a comparison between Apache Kafka on Confluent Cloud and Kubecost based on real PeerSpot user reviews.

Find out in this report how the two AWS Marketplace solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

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To learn more, read our detailed Apache Kafka on Confluent Cloud vs. Kubecost Report (Updated: April 2025).
Buyer's Guide
Apache Kafka on Confluent Cloud vs. Kubecost
April 2025
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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 Kafka on Confluent C...
Ranking in AWS Marketplace
2nd
Average Rating
8.2
Number of Reviews
11
Ranking in other categories
No ranking in other categories
Kubecost
Ranking in AWS Marketplace
24th
Average Rating
9.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2025, in the AWS Marketplace category, the mindshare of Apache Kafka on Confluent Cloud is 0.8%, down from 3.4% compared to the previous year. The mindshare of Kubecost is 0.2%, down from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AWS Marketplace
 

Featured Reviews

Ritik Varshney - PeerSpot reviewer
Enhanced data streaming with reliable features and good analytics
Apache Kafka on Confluent Cloud provides an enhanced level of reliability and resources compared to Apache Kafka alone. It offers more features which are beneficial for our clients, including cluster linking, schema registry, error handling, and dead-letter queues. It significantly improves customer and publisher satisfaction, especially with topic integration and data streaming.
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DIRK UYTTERHOEVEN - PeerSpot reviewer
Identifies and eliminates overprovisioning of expensive resources like storage, highly scalable and offers performance
I like the overall product because I can select what monitoring should be enabled and whatnot. In our case, we really focus on performance because it's clear that the price is related to most performance setups. So the more performance, the more expensive. So we look into the performance that the customer needs, and then based upon that feedback from the remote control, we change the parameters. And even the end user will not notice it is not using it, so we just make money without any impact on the end users.
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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

"Kafka provides handy properties that allow us to directly configure the data, whether to keep it or discard it after use."
"The state-saving feature is very much appreciated. It allows me to rewind a certain process if I see an error and then reprocess it."
"Kafka and Confluent Cloud have proven to be cost-effective, especially when compared to other tools. In a recent BI integration program over the past year, we assessed multiple use cases spanning ship-to-shore and various Azure integrations. Our findings revealed that Confluent Kafka performed exceptionally well, standing out alongside Genesys and Azure Event Hubs. While these three are top contenders, the choice among other tools depends on the specific use case and project requirements. The customer initially used tools like SMQs, FITRA, and Stream for real-time data processing. However, after our recommendation, Confluent Cloud proved to be a superior choice, capable of replacing these three tools and simplifying their data infrastructure. This shift to a single tool, Confluent Cloud, streamlined their operations, making maintenance and management more efficient for their internal projects."
"The product's installation phase is pretty straightforward for us since we know how to use it."
"Overall, I think it's a good experience. Apache Kafka can be quite complex and difficult to maintain on your own, so using Apache Kafka on Confluent Cloud makes it much easier to use it without worrying about setup and maintenance."
"Confluent Cloud handles data volume pretty well."
"In case of huge transactions on the web or mobile apps, it helps you capture real-time data and analyze it."
"Apache Kafka on Confluent Cloud is more reliable and frequent to use compared to Apache Kafka."
"It offers a detailed examination of your cluster, including the types of instances utilized, allocated CPU and RAM, and resource distribution for specific applications."
"The price is reasonable, considering the value it delivers."
"I mostly like the dashboards."
 

Cons

"Some areas for improvement in Apache Kafka on Confluent Cloud include issues faced during migration with Kubernetes pods."
"There could be an in-built feature for data analysis."
"There's one thing that's a common use case, but I don't know why it's not covered in Kafka. When a message comes in, and another message with the same key arrives, the first version should be deleted automatically."
"The solution is expensive."
"The administration port could be more extensive."
"There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations."
"Regarding real-time data usage, there were challenges with CDC (Change Data Capture) integrations. Specifically, with PyTRAN, we encountered difficulties. We recommended using our on-premises Kaspersky as an alternative to PyTRAN for that specific use case due to issues with CDC store configuration and log reading challenges with the iton components."
"Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges."
"Faster monitoring could potentially improve overall stability in the production environment."
"The integration with other solutions could be improved."
"There is a significant potential for enhancing it through the incorporation of advanced technologies like AI and generative AI."
 

Pricing and Cost Advice

"I think the pricing is fair, but Confluent requires a little bit more thinking because the price can go up really quickly when it comes to premium connectors."
"I consider that the product's price falls under the middle range category."
"Regarding pricing, Apache Kafka on Confluent Cloud is not a cheap tool. The right use case would justify the cost. It might make sense if you have a high volume of data that you can leverage to generate value for the business. But if you don't have those requirements, there are likely cheaper solutions you could use instead."
"The cost is cheap. Kubecost has an open-source core."
"The cost of the tool may seem nominal compared to the potential savings in infrastructure expenses."
"The real savings come from using Kubecost features like autoscaling and serverless functions to optimize your resource usage. If you treat it like a data center migration without fine-tuning, it might cost more."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Transportation Company
7%
Computer Software Company
7%
Manufacturing Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Apache Kafka on Confluent Cloud?
Kafka and Confluent Cloud have proven to be cost-effective, especially when compared to other tools. In a recent BI integration program over the past year, we assessed multiple use cases spanning s...
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What needs improvement with Apache Kafka on Confluent Cloud?
The ability to implement request-response communication on Apache Kafka ( /products/apache-kafka-reviews ) needs improvement. The schema registry is a bit misleading in terms of its location and ho...
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What is your primary use case for Apache Kafka on Confluent Cloud?
We send events to Apache Kafka on Confluent Cloud ( /products/apache-kafka-on-confluent-cloud-reviews ) for microservices and in an event-driven system. We are building an event-driven system, and ...
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What do you like most about Kubecost?
The price is reasonable, considering the value it delivers.
See all answers
What is your experience regarding pricing and costs for Kubecost?
The price is reasonable, considering the value it delivers. In all honesty, once you have your optimal design, you could just turn it off and then activate it maybe once every six months or once ev...
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What needs improvement with Kubecost?
In future releases, I would like to see faster monitoring because it could potentially improve overall stability in the production environment.
See all answers
 

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Product Reports

Buyer's Guide
Apache Kafka on Confluent Cloud
April 2025
Apache Kafka on Confluent Cloud reportDownload Apache Kafka on Confluent Cloud product report
Buyer's Guide
AWS Marketplace
April 2025
Kubecost reportDownload Kubecost product report
 

Also Known As

No data available
Kubecost - Amazon EKS cost monitoring
 

Overview

Apache Kafka on Confluent Cloud enables organizations to perform real-time data streaming and processing, integrating user data, and managing large transaction volumes efficiently.

Organizations leverage Apache Kafka on Confluent Cloud for several applications such as capturing change data, handling IoT workloads, and fostering data migration and microservices. It is instrumental in publishing and managing data across multiple platforms, ensuring both high throughput and seamless log management. Confluent Cloud's features like scalability, efficient transaction management, and cost-effectiveness, combined with seamless integration with multiple data tools, make it a preferred choice for real-time data processing tasks.

What are the key features?

  • Scalability: Easily scale up or down based on demand.
  • Efficient transaction management: Manage transactions smoothly.
  • Cost-effectiveness: Optimize costs without compromising performance.
  • Real-time data capture: Capture data in real-time with ease.
  • State-saving: Save states efficiently to support various processes.
  • Message processing speed: Fast processing of messages ensures quick data handling.
  • Topic flexibility: Flexibility in managing topics caters to different data needs.

What benefits and ROI should you look for?

  • Seamless integration: Integrate effortlessly with major data tools.
  • Streamlined operations: Reduce the number of tools required for data processing and streamline maintenance.
  • High throughput: Maintain high throughput across platforms.
  • Seamless log management: Effective management of logs ensures operational efficiency.


In specific industries, such as finance, real-time data processing is crucial for handling high volumes of transactions and location tracking. In retail, it integrates user data and manages inventory systems efficiently. IoT applications benefit from Apache Kafka on Confluent Cloud by capturing and processing massive data streams from connected devices in real-time.

Confluent

Kubecost provides real-time cost visibility and insights for teams using Kubernetes, helping you continuously reduce your cloud costs.
Breakdown costs by any Kubernetes concepts, including deployment, service, namespace label, and more. View costs across multiple clusters in a single view or via a single API endpoint.
Receive dynamic recommendations for reducing spend without sacrificing performance. Prioritize key infrastructure or application changes for improving resource efficiency and reliability.
Quickly catch cost overruns and infrastructure outage risks before they become a problem with real-time notifications. Preserve engineering workflows by integrating with tools like Microsoft Teams and Slack.

Kubecost
Buyer's Guide
Apache Kafka on Confluent Cloud vs. Kubecost
April 2025
Free Report: Apache Kafka on Confluent Cloud vs. Kubecost
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We monitor all AWS Marketplace reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.