Apache Kafka on Confluent Cloud Reviews

Name: Apache Kafka on Confluent Cloud
Brand: Confluent
Rating: 4 (9 reviews)

4.1 out of 5

9 reviews
100% willing to recommend

What is Apache Kafka on Confluent Cloud?

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

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Apache Kafka on Confluent Cloud is the #4 ranked solution in top AWS Marketplace solutions. PeerSpot users give Apache Kafka on Confluent Cloud an average rating of 8.2 out of 10. Apache Kafka on Confluent Cloud is most commonly compared to Security Onion: Apache Kafka on Confluent Cloud vs Security Onion. Apache Kafka on Confluent Cloud is popular among the large enterprise segment, accounting for 76% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 14% of all views.

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Apache Kafka on Confluent Cloud

November 2024

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Featured reviews

Anantharaman Ganesan

Managing Director at Aara Tech Private Limited

Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges. With other products, specifically non-Apache ones or Microsoft, our company had created some wrapper classes around them. The integration issues of Apache Kafka revolve around other products like Tomcat, other web servers, or Node.js and .NET Core-related areas. After creating some wrapper classes around them, we were able to get the information we wanted. My company has not used any AI features in the product, but I would like to see AI features in the product because they currently help generate real-time content. AI can help our company slowly create some LLM. My company is not currently implementing any AI features, but I see that there will be a lot of opportunities to use such functionalities. I have experience with Databricks, for which I have used AI.

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Shubham Yadav

Backend Developer at Mindstix Softwares

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. We want to keep only one instance of a message at any given time, the latest one. However, Kafka doesn't have this functionality built-in. It keeps all the data, and we have to manually delete the older versions. So, I would like to have only one instance of messages, based on the keys. If the key is the same, there should always be the latest message present instead of all versions of that message.

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Arucy Lionel

Co-Founder at Afriziki

I use it for real-time processing workloads. So, in some instances, it's like IoT data. We need to put it into a data lake. However, we are using Redpanda, which is still a Kafka protocol. Lots of real-time processing and high-velocity data are the use cases I'm happy with the scalability and…

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Apache Kafka on Confluent Cloud mindshare

As of November 2024, the mindshare of Apache Kafka on Confluent Cloud in the AWS Marketplace category stands at 3.4%, down from 3.7% compared to the previous year, according to calculations based on PeerSpot user engagement data.

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Last updated Oct 1, 2024

Valuable Features

Apache Kafka on Confluent Cloud offers features such as real-time data capture and analysis, scalability, cost-effectiveness, flexibility in replaying topics, efficient integration with other tools, seamless handling of large and small data volumes, and streamlined operations. It supports diverse configurations for various use cases, simplifies maintenance and management, and provides robust topic and partition management. It enhances microservices architecture and facilitates efficient data pipelines, making it easier to use without setup and maintenance concerns.

"Confluent Cloud handles data volume pretty well."
"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."
"The product's installation phase is pretty straightforward for us since we know how to use it."

Room for Improvement

Apache Kafka on Confluent Cloud needs an in-built data analysis feature, improved memory management and reduced latency spikes. Challenges with CDC integrations and issues with PyTRAN are noted. More integration ease with Microsoft tools and automatic message deletion based on keys are desired. Administrative improvements, easier event state management, and access to premium connectors are needed. Users also suggest AI features for real-time content generation and highlight the high cost.

"There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations."
"The solution is expensive."
"Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges."

ROI

Apache Kafka on Confluent Cloud provided a significant return on investment, particularly in the maintenance space, by eliminating the need for platform management. Substantial improvements at year's end included reduced issue resolution needs and minimized deployment teams due to Confluent's support model. AWS required deploying the right people away from other initiatives. Clients benefited from fast, reliable cloud streaming for data processing.

Pricing

Pricing for Apache Kafka on Confluent Cloud is perceived as fair and falls within the middle range category. Users appreciate the pay-as-you-use model, finding it affordable given its value, especially when high data volumes are beneficial. However, it's noted that premium connectors can significantly increase costs, and enterprises in development stages might find it cost-prohibitive without high-volume data use cases to justify the expense.

"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

Apache Kafka on Confluent Cloud is primarily used for real-time data streaming, processing, and integration. Companies utilize it for capturing user data, IoT data, data lake ingestion, and event-driven architectures. Additional applications include microservices integration, CDC processes, high-velocity data management, log-related tasks, and improving data quality. Use cases span various domains such as system development, operations, data management, and system quality. It is also employed for handling large volumes of data in specific industries like insurance.

Deployment

The initial setup of Apache Kafka on Confluent Cloud involves effort but is simplified by good documentation. Users find the process straightforward, diverse between hours to a year depending on the specifics. Some experienced no trouble, as AWS and Confluent aid significantly. Configuring parameters and understanding design require familiarity. Integration choices, such as networking setups, can impact functionality and visibility. Opinions vary from easy due to provided documents to challenging based on company's errors.

Scalability

Apache Kafka on Confluent Cloud is highly scalable, handling large user bases effectively. Users report that it scales storage based on needs and performs well with big data. While some note minor reliability issues during scaling, it maintains stable performance. Large enterprises find it easy to scale with minimal manual management. Performance during data scaling is also praised, with many rating its scalability 8 or 9 out of 10.

Stability

Feedback on Apache Kafka on Confluent Cloud's stability is mixed, ranging from great to problematic. Some rate its stability highly, praising its uptime and reliability, while others highlight issues with latency spikes, resource consumption, and handling increased traffic. Users also mention challenges with dashboard access and topic management. Despite some positive experiences without major issues, varying stability ratings suggest areas for improvement.

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

By visitors reading reviews

Top industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

Transportation Company

Government

Healthcare Company

Comms Service Provider

Outsourcing Company

Construction Company

University

Educational Organization

Logistics Company

Manufacturing Company

Media Company

Wholesaler/Distributor

Consumer Goods Company

Aerospace/Defense Firm

Energy/Utilities Company

Individual & Family Service

Hospitality Company

Insurance Company

Legal Firm

Recreational Facilities/Services Company

Retailer

Leisure / Travel Company

Venture Capital & Private Equity Firm

Compare Apache Kafka on Confluent Cloud with alternative products

Learn more about Apache Kafka on Confluent Cloud

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.