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Apache Kafka on Confluent Cloud vs Saturn Cloud comparison

 

Comparison Buyer's Guide

Executive Summary

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 AWS Marketplace
2nd
Average Rating
8.4
Number of Reviews
12
Ranking in other categories
No ranking in other categories
Saturn Cloud
Ranking in AWS Marketplace
17th
Average Rating
10.0
Reviews Sentiment
7.5
Number of Reviews
6
Ranking in other categories
Data Science Platforms (9th)
 

Mindshare comparison

As of June 2025, in the AWS Marketplace category, the mindshare of Apache Kafka on Confluent Cloud is 0.9%, down from 3.4% compared to the previous year. The mindshare of Saturn Cloud is 0.1%, down from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AWS Marketplace
 

Featured Reviews

Ritik Varshney - PeerSpot reviewer
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.
Filip Stefanovski - PeerSpot reviewer
Easy to use with good performance and collaborative features
My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer. Users could bid on unused compute capacity, potentially leading to significant cost savings during off-peak hours or for less time-critical tasks. Spot instances empower users with tighter budgets or fluctuating workloads to strategically leverage lower-cost resources for development, experimentation, and background tasks. This frees up on-demand instances for truly time-sensitive work.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Kafka provides handy properties that allow us to directly configure the data, whether to keep it or discard it after use."
"Confluent Cloud handles data volume pretty well."
"In case of huge transactions on the web or mobile apps, it helps you capture real-time data and analyze it."
"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 product's installation phase is pretty straightforward for us since we know how to use it."
"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 state-saving feature is very much appreciated. It allows me to rewind a certain process if I see an error and then reprocess it."
"Apache Kafka on Confluent Cloud is more reliable and frequent to use compared to Apache Kafka."
"The feature I like the most about Saturn Cloud is that it has lightning-fast CPUs."
"It didn't take long to see that Saturn Cloud could scale with my needs, providing more resources when required."
"They provide a centralized space for data, code, and results."
"Saturn Cloud supports GPU as part of the environment, which is essential for many computational tasks in machine learning projects. It also allows us to edit the environment, including the image, before we start the cloud resources. This feature lets us quickly set up the environment without the hassle of moving the data and code to another cloud device."
"It offered an excellent development environment while not touching our production cloud resources."
"There is plenty of computational resources (both GPU, CPU and disk space)."
 

Cons

"Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges."
"Some areas for improvement in Apache Kafka on Confluent Cloud include issues faced during migration with Kubernetes pods."
"There could be an in-built feature for data analysis."
"The administration port could be more extensive."
"The solution is expensive."
"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."
"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."
"There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations."
"My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer."
"Providing more detailed and beginner-friendly documentation, especially for advanced features, could greatly enhance the user experience."
"Saturn Cloud should include prebuilt images for advanced data science packages like LightGBM in the next release. If possible, they should also provide a Kaggle image, which contains the most common Python packages used in machine learning."
"It would be nice to have more hardware category options, like TPU coprocessors or ARM64 CPUs."
"We'd like to have the capability for installing more libraries."
"Public Clouds integration and sandbox environments would be a true game changer."
 

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."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
8%
Educational Organization
7%
Manufacturing Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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 do you like most about Saturn Cloud?
There is plenty of computational resources (both GPU, CPU and disk space).
What needs improvement with Saturn Cloud?
My main suggestion for improvement centers on pricing. Introducing a tier modelled after AWS spot instances would be a game-changer. Users could bid on unused compute capacity, potentially leading ...
What is your primary use case for Saturn Cloud?
I'm leveraging a cloud-based platform for competitive machine learning. Tight deadlines and resource-intensive models demand powerful hardware. The cloud provides scalable GPUs and RAM, letting me ...
 

Overview

 

Sample Customers

Information Not Available
Nvidia, Snowflake, Kaggle, Faeth, Advantest, Stanford University, Senseye and more.
Find out what your peers are saying about Apache Kafka on Confluent Cloud vs. Saturn Cloud and other solutions. Updated: April 2025.
857,028 professionals have used our research since 2012.