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Apache Kafka on Confluent Cloud pros and cons

Vendor: Confluent
4.3 out of 5
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Pros & Cons summary

Apache Kafka on Confluent Cloud excels in BI integrations, simplifying data infrastructure by replacing various tools, enhancing management. It handles large data volumes efficiently and supports data configuration options, boosting usability without extra maintenance. While offering scalability and resilience, it faces challenges in CDC integrations and monitoring. Certain premium connectors are inaccessible, and feature improvements are needed for automatic message deletion with identical keys and in-built data analysis functions.

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Prominent pros & cons

PROS

Apache Kafka on Confluent Cloud helps capture real-time data and analyze it effectively in large transactions.
It is cost-effective and excels in various integrations, including ship-to-shore and Azure.
Confluent Cloud simplifies data infrastructure, replacing multiple tools and enhancing maintenance and management efficiency.
Its state-saving feature enables error correction and process reprocessing.
Streaming and event capabilities contribute to its scalability and resiliency.

CONS

There are challenges with CDC integrations, specifically with PyTRAN, leading to difficulties with CDC store configuration and log reading challenges.
There are limitations with premium connectors in Confluent, which are not accessible in the marketplace.
The integration with other Microsoft tools presents challenges for some users.
The administration port could be more extensive.
There are issues faced during migration with Kubernetes pods.
 

Apache Kafka on Confluent Cloud Pros review quotes

reviewer2237604 - PeerSpot reviewer
May 24, 2024
Confluent Cloud handles data volume pretty well.
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Shubham Yadav - PeerSpot reviewer
Jul 24, 2024
Kafka provides handy properties that allow us to directly configure the data, whether to keep it or discard it after use.
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FABIO LUIS VELLOSO DA SILVA - PeerSpot reviewer
Sep 9, 2025
It's very fast and helps us to create the project, guarantee the message delivery, and the performance.
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Apache Kafka on Confluent Cloud
September 2025
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Anantharaman Ganesan - PeerSpot reviewer
Aug 1, 2024
The product's installation phase is pretty straightforward for us since we know how to use it.
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Ritik Varshney - PeerSpot reviewer
Nov 21, 2024
Apache Kafka on Confluent Cloud is more reliable and frequent to use compared to Apache Kafka.
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Tom Hug - PeerSpot reviewer
Jun 4, 2024
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.
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DB
Nov 29, 2023
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.
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reviewer2751003 - PeerSpot reviewer
Aug 19, 2025
Some of the best features with Apache Kafka on Confluent Cloud are streaming and event capabilities, which are important due to scalability and resiliency.
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reviewer2534229 - PeerSpot reviewer
Aug 16, 2024
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.
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SP
Oct 25, 2023
In case of huge transactions on the web or mobile apps, it helps you capture real-time data and analyze it.
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Apache Kafka on Confluent Cloud Cons review quotes

reviewer2237604 - PeerSpot reviewer
May 24, 2024
There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations.
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Shubham Yadav - PeerSpot reviewer
Jul 24, 2024
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.
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FABIO LUIS VELLOSO DA SILVA - PeerSpot reviewer
Sep 9, 2025
The clustering is a little hard for juniors and clients. It's suitable for senior engineers, but the configuration and clustering are very hard for juniors.
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Buyer's Guide
Apache Kafka on Confluent Cloud
September 2025
Free Report: Apache Kafka on Confluent Cloud Reviews and More
Learn what your peers think about Apache Kafka on Confluent Cloud. Get advice and tips from experienced pros sharing their opinions. Updated: September 2025.
DOWNLOAD NOW
867,497 professionals have used our research since 2012.
Anantharaman Ganesan - PeerSpot reviewer
Aug 1, 2024
Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges.
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Ritik Varshney - PeerSpot reviewer
Nov 21, 2024
Some areas for improvement in Apache Kafka on Confluent Cloud include issues faced during migration with Kubernetes pods.
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Tom Hug - PeerSpot reviewer
Jun 4, 2024
The administration port could be more extensive.
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DB
Nov 29, 2023
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.
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reviewer2751003 - PeerSpot reviewer
Aug 19, 2025
In terms of improvements, observability and monitoring are areas that could be enhanced. They are lacking in terms of observability and monitoring compared to other products.
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reviewer2534229 - PeerSpot reviewer
Aug 16, 2024
The solution is expensive.
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SP
Oct 25, 2023
There could be an in-built feature for data analysis.
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