Try our new research platform with insights from 80,000+ expert users
Apache Kafka on Confluent Cloud Logo

Apache Kafka on Confluent Cloud Reviews

Vendor: Confluent
4.2 out of 5
Leave a review

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.

Get the Apache Kafka on Confluent Cloud Buyer's Guide and find out what your peers are saying about Apache Kafka on Confluent Cloud and more!
Buyer's Guide
Apache Kafka on Confluent Cloud
August 2025
Get the report
Helped 865,670 peers since 2012

Featured Apache Kafka on Confluent Cloud reviews

Read more reviews

Apache Kafka on Confluent Cloud mindshare

As of August 2025, the mindshare of Apache Kafka on Confluent Cloud in the Streaming Analytics category stands at 0.0%, according to calculations based on PeerSpot user engagement data.
Streaming Analytics

PeerResearch reports based on Apache Kafka on Confluent Cloud reviews

TypeTitleDate
CategoryStreaming AnalyticsAug 24, 2025Download
ProductReviews, tips, and advice from real usersAug 24, 2025Download
ComparisonApache Kafka on Confluent Cloud vs DatabricksAug 24, 2025Download
ComparisonApache Kafka on Confluent Cloud vs Amazon KinesisAug 24, 2025Download
ComparisonApache Kafka on Confluent Cloud vs ConfluentAug 24, 2025Download
 
 
Key learnings from peers

Valuable Features

Apache Kafka on Confluent Cloud offers real-time data handling, seamless integrations, and exceptional scalability. It provides advanced features like schema registry, partitions, and error handling. Users appreciate its ease of managing data pipelines, reliable performance across cloud platforms, and stress-free maintenance of Kafka clusters. Its resilience, order guarantee, and serverless architecture enhance operational efficiency, allowing enterprises to connect disparate data sources and simplify domain event handling.
  • "Some of the best features with Apache Kafka on Confluent Cloud are streaming and event capabilities, which are important due to scalability and resiliency."
  • "Apache Kafka on Confluent Cloud is more reliable and frequent to use compared to Apache Kafka."
  • "Confluent Cloud handles data volume pretty well."

Room for Improvement

Apache Kafka on Confluent Cloud requires improvements in data analysis features, integrating with Microsoft tools, and CDC store configuration. Users face difficulties in deploying custom applications, managing event states, and automatically deleting outdated messages. There are challenges with migration using Kubernetes pods and enhancing real-time data processing capabilities. Observability and monitoring require attention, along with a desire for AI feature integration. Costs and support for high-end features are also areas for improvement.
  • "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."
  • "Some areas for improvement in Apache Kafka on Confluent Cloud include issues faced during migration with Kubernetes pods."
  • "There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations."

ROI

Apache Kafka on Confluent Cloud provided significant maintenance savings by eliminating platform management tasks. Teams reallocated resources efficiently because its support model resolved issues promptly, unlike AWS that required specialized personnel. Clients benefited from cloud streaming's speed and reliability, while the system's real-time capabilities delivered substantial business value, reducing infrastructure costs significantly. Though expensive and challenging to adopt widely, it ensured stability and scalability with impressive ROI, depending on deployed applications and benefits received.

Pricing

Enterprise users find Apache Kafka on Confluent Cloud pricing fair but acknowledge that costs can rise quickly, especially with premium connectors. While the tool isn't cheap, it offers reasonable pricing for high data volumes, appealing for cases generating business value. Flexible pricing and resource-based billing help cater to diverse needs, yet users need to manage costs carefully, approving usage to avoid unnecessary expenses. Pricing can range from 30,000 to 60,000 euros annually.
  • "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

Companies primarily utilize Apache Kafka on Confluent Cloud for real-time data streaming and integration across various domains, including microservices communication, real-time transaction processing, and CDC processes. It efficiently handles data from point of generation to consumption and supports microservices, log management, and event management for industries like finance and insurance. Businesses leverage its capabilities for data analytics, enhancing data quality, and enabling real-time location tracking in cloud and on-premise environments.

Service and Support

Customer service and support for Apache Kafka on Confluent Cloud are positively acknowledged. Users rate the support around eight out of ten when using Confluent's tools, with some mixed-product experiences rating it six. Technical expertise in addressing bugs is commendable. Some challenges arise, requiring reminders about initial objectives. The original Apache Kafka team contributes, ensuring strong backing. Many users primarily rely on forums and blogs for resolving issues, highlighting capable customer service assistance.

Deployment

The initial setup of Apache Kafka on Confluent Cloud varies from easy to challenging. Some find it straightforward, with sufficient documentation aiding the process, while others face difficulties such as configuring values and network setup. Timeframes range from hours to a year, often depending on use cases. Users appreciate the documentation and support from Confluent and AWS, facilitating a smoother deployment experience. Networking choices can impact visibility and functionality within the platform.

Scalability

Apache Kafka on Confluent Cloud demonstrates high scalability with the ability to scale horizontally, enabling efficient management of large data volumes. Users appreciate its easy adaptability to fluctuating needs, though some mention reliability concerns during scaling. The platform supports multi-cloud operations and automation, minimizing the need for extensive management. While some experience data loss during scaling adjustments, others find it highly efficient and place it within their top criteria for technology stack selection.

Stability

Users consistently rate Apache Kafka on Confluent Cloud highly for stability, with most scores around eight to nine. They appreciate its 99.99% availability and find it reliable with few issues in production. Although setup can be challenging, and high traffic can cause unresponsiveness, proactive monitoring and alerts help maintain operations. While some experience problems when topic numbers increase, others report no major bugs, expressing satisfaction with its progressive capabilities.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Apache Kafka on Confluent Cloud Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
8%
Educational Organization
7%
Computer Software Company
6%
Government
6%
Construction Company
5%
Retailer
5%
Insurance Company
5%
Comms Service Provider
3%
Energy/Utilities Company
3%
Healthcare Company
3%
Recreational Facilities/Services Company
3%
Transportation Company
3%
University
3%
Wholesaler/Distributor
3%
Consumer Goods Company
3%
Pharma/Biotech Company
3%
Real Estate/Law Firm
3%
Outsourcing Company
2%
Performing Arts
2%
Logistics Company
2%
Legal Firm
1%
Aerospace/Defense Firm
1%
Media Company
1%
Non Profit
1%
Individual & Family Service
1%
Museum Or Institution
1%
Wellness & Fitness Company
1%
Renewables & Environment Company
1%
Hospitality 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.

Related questions

  • 35
How do you select the right cloud ETL tool?
  • 22
What is the best streaming analytics tool?
  • 44
What are the benefits of streaming analytics tools?
  • 55
What features do you look for in a streaming analytics tool?
  • 12
When evaluating Streaming Analytics, what aspect do you think is the most important to look for?
  • 15
Why is Streaming Analytics important for companies?

Product Categories

Product Categories
Streaming Analytics