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Apache Kafka on Confluent Cloud vs TetraScience comparison

Confluent and TetraScience are both solutions in the AWS Marketplace category. Confluent is ranked #2 with an average rating of 8.3, while TetraScience is ranked #99 with an average rating of 6.5. Additionally, 100% of Confluent users are willing to recommend the solution, compared to 50% of TetraScience users who would recommend it.
Apache Kafka on Confluent C...
Read 11 Apache Kafka on Confluent Cloud reviews
  • 530 Views
  • 422 Comparison Views
100% willing to recommend
TetraScience
Read 2 TetraScience reviews
  • 98 Views
  • 29 Comparison Views
50% willing to recommend
 

Comparison Buyer's Guide

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Executive Summary
We performed a comparison between Apache Kafka on Confluent Cloud and TetraScience based on real PeerSpot user reviews.

Find out in this report how the two AWS Marketplace solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

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To learn more, read our detailed Apache Kafka on Confluent Cloud vs. TetraScience Report (Updated: March 2025).
Buyer's Guide
Apache Kafka on Confluent Cloud vs. TetraScience
March 2025
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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 AWS Marketplace
2nd
Average Rating
8.2
Number of Reviews
11
Ranking in other categories
No ranking in other categories
TetraScience
Ranking in AWS Marketplace
99th
Average Rating
6.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

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.
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Varun Khandavalli - PeerSpot reviewer
Efficient data integration and good automation with challenging configurability
The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met. The application also lacks capabilities within its terminal commands that are not available in their GUI. It requires a lot of configurability, which could be streamlined for an enterprise application user.
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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

"Kafka provides handy properties that allow us to directly configure the data, whether to keep it or discard it after use."
"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."
"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."
"Apache Kafka on Confluent Cloud is more reliable and frequent to use compared to Apache Kafka."
"Confluent Cloud handles data volume pretty well."
"The ingestion engines were pretty good."
"The crawler agents they provide, as well as TetraScience exclusive parsers, allow for specific instruments that we use in our labs with proprietary formats to extract data and put it into more standard formats for various purposes."
 

Cons

"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."
"There could be an in-built feature for data analysis."
"The solution is expensive."
"Maybe in terms of Apache Kafka's integration with other Microsoft tools, our company faced some challenges."
"The administration port could be more extensive."
"Some areas for improvement in Apache Kafka on Confluent Cloud include issues faced during migration with Kubernetes pods."
"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."
"The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met."
"While functional during ingestion workflows, the automation toolkit required manual processes."
 

Pricing and Cost Advice

"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 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."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
8%
Computer Software Company
6%
Government
6%
No data available
 

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...
See all answers
What needs improvement with Apache Kafka on Confluent Cloud?
The ability to implement request-response communication on Apache Kafka ( /products/apache-kafka-reviews ) needs improvement. The schema registry is a bit misleading in terms of its location and ho...
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What is your primary use case for Apache Kafka on Confluent Cloud?
We send events to Apache Kafka on Confluent Cloud ( /products/apache-kafka-on-confluent-cloud-reviews ) for microservices and in an event-driven system. We are building an event-driven system, and ...
See all answers
What needs improvement with TetraScience?
The application has a difficult-to-use parsing capability, which requires a lot of reengineering when the use case isn't specifically met. The application also lacks capabilities within its termina...
See all answers
What is your primary use case for TetraScience?
TetraScience is a platform that integrates instruments into a laboratory environment into other software applications that can help leverage the data. In most pharma companies, the application is u...
See all answers
What advice do you have for others considering TetraScience?
I would approach with caution. The platform has a high knowledge gap and the proprietary nature of its parsers and crawling agents. Before approaching TetraScience, have your use case in hand and u...
See all answers
 

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Product Reports

Buyer's Guide
Apache Kafka on Confluent Cloud
April 2025
Apache Kafka on Confluent Cloud reportDownload Apache Kafka on Confluent Cloud product report
Buyer's Guide
AWS Marketplace
April 2025
TetraScience reportDownload TetraScience product report
 

Overview

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

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.

Confluent

TetraScience liberates, unifies, and transforms your raw data into more-than-FAIR, AI-native data.
We bring this AI-native data to life in a rapidly growing suite of next-generation lab data management solutions, scientific use cases, and AI-based scientific outcomes.
Only the Tetra Scientific Data and AI Cloud can liberate your data, engineer it for your most demanding scientific use cases and AI initiatives, and future-proof it so you’re never locked into vendor walled gardens again.

TetraScience
Buyer's Guide
Apache Kafka on Confluent Cloud vs. TetraScience
March 2025
Free Report: Apache Kafka on Confluent Cloud vs. TetraScience
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