Apache Kafka on Confluent Cloud vs Starburst Enterprise comparison

Apache Kafka on Confluent Cloud vs. Starburst Enterprise

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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 Streaming Analytics

10th

Average Rating

8.4

Reviews Sentiment

5.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Starburst Enterprise

Ranking in Streaming Analytics

15th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Science Platforms (12th)

Mindshare comparison

As of August 2025, in the Streaming Analytics category, the mindshare of Apache Kafka on Confluent Cloud is 0.0%. The mindshare of Starburst Enterprise is 3.6%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

Ritik Varshney

Scholar Trainee/Project Engineer at Wipro Limited

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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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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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

"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."

"Apache Kafka on Confluent Cloud is more reliable and frequent to use compared to Apache Kafka."

"Confluent Cloud handles data volume pretty well."

"Some of the best features with Apache Kafka on Confluent Cloud are streaming and event capabilities, which are important due to scalability and resiliency."

"Kafka provides handy properties that allow us to directly configure the data, whether to keep it or discard it after use."

"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 state-saving feature is very much appreciated. It allows me to rewind a certain process if I see an error and then reprocess it."

"In case of huge transactions on the web or mobile apps, it helps you capture real-time data and analyze it."

More Apache Kafka on Confluent Cloud pros

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

"It's very scalable, fast performing, and supports many catalogs."

Cons

"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."

"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."

"Some areas for improvement in Apache Kafka on Confluent Cloud include issues faced during migration with Kubernetes pods."

"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."

"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."

"Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges."

More Apache Kafka on Confluent Cloud cons

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

"There should be support for REST API data sources to access data from the web."

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."

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Manufacturing Company

Computer Software Company

Government

Financial Services Firm

43%

Computer Software Company

Energy/Utilities Company

Government

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...

What needs improvement with Apache Kafka on Confluent Cloud?

I think what I would improve about the solution is the cost, mostly. From my standpoint, it's the cost. From an engineering perspective, it works really well. There's always room for improvement. O...

What is your primary use case for Apache Kafka on Confluent Cloud?

We find that the best features include using the CDC functionality with the connector to take the data from our SQL database and publish it to many consumers. Any changes enable us to easily publis...

What is your experience regarding pricing and costs for Starburst Enterprise?

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

What needs improvement with Starburst Enterprise?

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

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Product Reports

Apache Kafka on Confluent Cloud

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Data Science Platforms

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Overview

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.

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.

Confluent

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

Starburst

Apache Kafka on Confluent Cloud vs. Starburst Enterprise