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Apache Kafka on Confluent Cloud Reviews

Vendor: Confluent
4.3 out of 5
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What is Apache Kafka on Confluent Cloud?

Apache Kafka on Confluent Cloud provides real-time data streaming with seamless integration, enhanced scalability, and efficient data processing, recognized for its real-time architecture, ease of use, and reliable multi-cloud operations while effectively managing large data volumes.

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Buyer's Guide
Apache Kafka on Confluent Cloud
January 2026
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Apache Kafka on Confluent Cloud mindshare

As of January 2026, the mindshare of Apache Kafka on Confluent Cloud in the Streaming Analytics category stands at 0.5%, according to calculations based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka on Confluent Cloud0.5%
Apache Flink12.3%
Databricks10.0%
Other77.2%
Streaming Analytics

PeerResearch reports based on Apache Kafka on Confluent Cloud reviews

TypeTitleDate
CategoryStreaming AnalyticsJan 10, 2026Download
ProductReviews, tips, and advice from real usersJan 10, 2026Download
ComparisonApache Kafka on Confluent Cloud vs DatabricksJan 10, 2026Download
ComparisonApache Kafka on Confluent Cloud vs Amazon KinesisJan 10, 2026Download
ComparisonApache Kafka on Confluent Cloud vs Azure Stream AnalyticsJan 10, 2026Download
 
 
Key learnings from peers
Last updated Nov 16, 2025

Valuable Features

Apache Kafka on Confluent Cloud offers scalability, resilience, and seamless integration with external systems. Its features like schema registry, cluster linking, and error handling enhance functionality. Users benefit from real-time data processing, topic configurations, and partitions, making operations efficient. The platform's event streaming capabilities, multi-cloud support, and robust API management streamline data infrastructure. Multi-language support and easy connection to various sources simplify workflows, while enhanced security and compliance ensure reliable data management.
  • "Confluent helped me to streamline all those logs into one place, and then I was consuming those logs that were produced, which made it very much easier because I know Kafka and using Confluent made it much simpler."
  • "The benefits that I have seen from having a real-time architecture include better velocity for developers; instead of developing many of those capabilities in each team, we can rely on Apache Kafka on Confluent Cloud to provide those functionalities we want, and the teams can focus on their own business instead of providing all sorts of APIs and dependencies to other domains, allowing everyone to run faster."
  • "The order guarantee of Apache Kafka on Confluent Cloud and the amount of throughput it can handle are valuable; the fact that the consumer pulls the data, not the broker, makes it more resilient and more reliable compared to other technologies."

Room for Improvement

Apache Kafka on Confluent Cloud could benefit from built-in data analysis features and improved CDC integration. Users experience challenges with premium connector availability, integration with Microsoft tools, and schema registry navigation. Cost and Kubernetes migration are also concerns. There are calls for enhanced real-time data processing, better request-response communication, and improved observability. Configuring clusters and error handling could be more user-friendly, and guidance for beginners would be helpful.
  • "I thought Confluent would stop me when I crossed the credits, but it did not, and then I got charged."
  • "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."
  • "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."

ROI

Organizations experienced significant return on investment from Apache Kafka on Confluent Cloud due to reduced platform management costs and the ability to allocate resources to other tasks. Teams benefited from Confluent support and saw decreased infrastructure expenses and enhanced stability. Real-time data processing accelerated speed to value and enabled new use cases. Despite its expense, meticulous implementation ensured positive outcomes related to stability and scalability, allowing businesses to offer clients reliable cloud streaming for data processing.

Pricing

Enterprise users note that Apache Kafka on Confluent Cloud has variable pricing, affected by use of premium connectors. While mid-range overall, some find it costly without high data volume needs. Recent product updates offer flexible and reasonable pricing for enterprise use cases. Pricing is fair, often between 30,000 to 60,000 euros annually, but requires careful cost management. Users benefit from free credits during initial testing but suggest enhanced credit alert mechanisms to avoid unexpected charges.
  • "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."
  • "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."
  • "I consider that the product's price falls under the middle range category."

Popular Use Cases

Organizations primarily use Apache Kafka on Confluent Cloud for real-time data streaming and integration, supporting a variety of use cases such as CDC processes, microservices communication, log monitoring, and transaction processing. They handle enormous data volumes swiftly for applications like IoT, financial transactions, and data analytics. Kafka's real-time capabilities are valued across sectors including retail and financial services. The cloud service facilitates easier data projection, event-driven systems, and real-time event handling with robust API functionalities.

Service and Support

Customer service and support for Apache Kafka on Confluent Cloud are generally praised, rated between six and ten out of ten, depending on tool compatibility. Many highlight timely, efficient responses, although some experience repetitive discussions. Prized is the involvement of original Apache Kafka contributors and good handling of queries, even during trials. Users appreciate the helpfulness but occasionally rely on external resources like forums and blogs to address issues.

Deployment

Users find Apache Kafka on Confluent Cloud's initial setup requires effort but becomes simpler once prerequisites are met. Opinions vary, with some achieving quick deployments and others needing months. Documentation and resources enhance ease, and support from Confluent and AWS aids setup. The user interface simplifies the process. Challenges include networking configurations and schema registries, yet most find it more manageable than open-source Apache Kafka, rating it favorably.

Scalability

Users find Apache Kafka on Confluent Cloud highly scalable, often rating it 8 or 9 out of 10. It adapts easily to varying needs, with notable efficiency in handling large data volumes across multi-cloud infrastructures. Horizontal scaling enhances performance and reliability, although some note room for improvement in offset management and reliability during scaling. It's effective for organizations needing minimal management overhead, aligning well with their current and future scalability requirements.

Stability

Apache Kafka on Confluent Cloud is generally considered stable. Most users give ratings between eight to nine out of ten, citing strong availability and reliable operations. A few have noted that configurations can be challenging and traffic spikes can cause responsiveness issues. Alerts for unusual activities help in maintaining stability. Although some encountered minor problems during setup, once properly configured, they experienced no major disruptions. Most believe Apache Kafka on Confluent Cloud maintains stable environments effectively.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
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Review data by company size

By reviewers
Company SizeCount
Small Business4
Midsize Enterprise3
Large Enterprise7
By reviewers
By visitors reading reviews
Company SizeCount
Small Business44
Midsize Enterprise23
Large Enterprise116
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
8%
Comms Service Provider
6%
Educational Organization
5%
Insurance Company
5%
Government
5%
Retailer
5%
Construction Company
5%
Outsourcing Company
4%
Computer Software Company
4%
Real Estate/Law Firm
4%
University
4%
Energy/Utilities Company
3%
Pharma/Biotech Company
3%
Transportation Company
3%
Recreational Facilities/Services Company
3%
Healthcare Company
3%
Wholesaler/Distributor
3%
Media Company
3%
Logistics Company
3%
Consumer Goods Company
2%
Performing Arts
2%
Non Profit
1%
Aerospace/Defense Firm
1%
Legal Firm
1%
Marketing Services Firm
1%
Individual & Family Service
1%
Hospitality Company
1%
Agriculture
1%
Museum Or Institution
1%
Renewables & Environment Company
1%
Wellness & Fitness Company
1%

Learn more about Apache Kafka on Confluent Cloud

Apache Kafka on Confluent Cloud is designed to handle large-scale data operations across different cloud environments. It supports real-time data streaming, crucial for applications in transaction processing, change data capture, microservices, and enterprise data movement. Users benefit from features like schema registry and error handling, which ensure efficient and reliable operations. While the platform offers extensive connector support and reduced maintenance, there are areas requiring improvement, including better data analysis features, PyTRAN CDC integration, and cost-effective access to premium connectors. Migrating with Kubernetes and managing message states are areas for development as well. Despite these challenges, it remains a robust option for organizations seeking to distribute data effectively for analytics and real-time systems across industries like retail and finance.

What are the key features of Apache Kafka on Confluent Cloud?
  • Seamless Integration: Connects with many data sources seamlessly.
  • Enhanced Scalability: Easily scales to manage increasing data loads.
  • Schema Registry: Maintains compatibility and evolution of schemas.
  • Offset Management: Tracks consumer progress efficiently.
  • Error Handling: Offers mechanisms to manage inaccuracies effectively.
  • Connector Support: Extensive connectors for diverse third-party tools.
What benefits should users seek in reviews?
  • Reliability: Consistent performance in multi-cloud environments.
  • Ease of Use: Simplified operations and maintenance.
  • Developer Efficiency: Streamlined features that save developers time.
  • Data Volume Handling: Capable of managing large-scale data streaming.

In industries like retail and finance, Apache Kafka on Confluent Cloud is implemented to manage real-time location tracking, event-driven systems, and enterprise-level data distribution. It aids in operations that require robust data streaming, such as CDC, log processing, and analytics data distribution, providing a significant edge in data management and operational efficiency.

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Product Categories

Product Categories
Streaming Analytics
 
Apache Kafka on Confluent Cloud Reviews Summary
Author infoRatingReview Summary
Lead Software Engineer at a tech vendor with 10,001+ employees4.5I used Apache Kafka on Confluent Cloud for unified log monitoring; it was easy to set up, supported multiple languages, and significantly improved our workflow, though better error handling and credit usage alerts would enhance the experience.
Partner at SouJava5.0I used Apache Kafka on Confluent Cloud with AWS for scalable asynchronous messaging; it's fast and reliable, but cluster setup is complex for juniors. Overall, it improved our system's performance, and I rate it 10 out of 10.
Chief Architect at a financial services firm with 10,001+ employees4.5I've used Apache Kafka on Confluent Cloud for nine years with event-driven applications, appreciating its streaming, scalability, and Stream Lineage features, though observability needs improvement. The setup is complex, but support is good and ROI depends on application use.
Global Vice President, Product Strategy & Gtm at NucleusTeq4.0No summary available
Fractional CTO at Tassei Tech4.5No summary available
Scholar Trainee/Project Engineer at Wipro Limited4.0I use Apache Kafka on Confluent Cloud for real-time data streaming and analytics. Its reliability and features like schema registry and error handling are beneficial. However, migration with Kubernetes pods could be improved. We chose it over Red Hat AMQ and Google's PubSub.
VP Engineering at a tech vendor with 1,001-5,000 employees4.5No summary available
Integration Solution Architect at a consultancy with 11-50 employees4.0In my company, we use Confluent Cloud for CDC processes, benefiting from minimal platform management and solid ecosystem integration. While some premium connectors are limited, the ease of deployment and enterprise features make it preferable to Amazon MSK.