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Apache Kafka on Confluent Cloud vs Coralogix 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 Streaming Analytics
12th
Average Rating
8.6
Reviews Sentiment
5.6
Number of Reviews
15
Ranking in other categories
No ranking in other categories
Coralogix
Ranking in Streaming Analytics
15th
Average Rating
8.4
Reviews Sentiment
6.6
Number of Reviews
13
Ranking in other categories
Application Performance Monitoring (APM) and Observability (21st), Log Management (21st), Security Information and Event Management (SIEM) (22nd), API Management (15th), Anomaly Detection Tools (1st), AI Observability (18th)
 

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Apache Kafka on Confluent Cloud is 0.5%. The mindshare of Coralogix is 0.7%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka on Confluent Cloud0.5%
Coralogix0.7%
Other98.8%
Streaming Analytics
 

Featured Reviews

AF
Lead Software Engineer at a tech vendor with 10,001+ employees
Has unified log streams from multiple systems and accelerated issue tracking through streamlined setup
I think Apache Kafka on Confluent Cloud can be improved by probably working more around Confluent or the tool. In my opinion, it should utilize the response structures in a better way or be able to detect if there is any variable or if there is any data structure that is mismatched, as it would be easier than us manually having to put in the exact name in order for it to match the response. Regarding additional improvements, I would say probably around error handling, where when we encounter errors specific to our response structures and everything, or the tables or anything of that nature, it would be better if we were prompted with better error handling mechanisms. I do not think there are any other improvements Apache Kafka on Confluent Cloud needs, aside from error handling and response structures.
Naveenkumar Lakshman - PeerSpot reviewer
Presales Engineer at Crayon AS
Centralized monitoring has improved real-time issue tracking and reduced root cause analysis time
One of the best features that Coralogix offers is that it is integration friendly. I can seamlessly work with different cloud providers including AWS, Azure, and GCP. I can monitor Kubernetes or Docker platforms as well, and I can integrate with the DevOps chain including Jenkins and all infrastructure code, Terraform, or Ansible. Coralogix has positively impacted my organization by providing a centralized console to monitor the dashboard, giving me rich flexibility to see different sorts of data that is spread across the logs, metrics, or traces, which are the typical pillars of the observability tool. I have the interface where I can use the drag-and-drop feature, and I can create different types of charts. Mainly, I have the line charts and time series ones that I generally use in many use cases, gauges, tables, pie charts, or markdown widgets. These are the ones generically available, and I can switch between the visualization types. I am getting the underlying query in that and can import and export dashboards built upon the JSON format. I can have my own APIs integrated with my dashboards as well, such as with Terraform, which is useful for scaling across my environments. Regarding root cause analysis, mainly what I can do is correlate across all of the layers because the main logs that I work on are storage-related, including CIFS, NFS, SAN traffic, and the metrics including storage, throughput, or VM resource usage. Being able to view logs, metrics, or traces available, I get all of these in one place, and I can do root cause analysis much quicker.

Quotes from Members

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

Pros

"Confluent Cloud handles data volume pretty well."
"Kafka provides handy properties that allow us to directly configure the data, whether to keep it or discard it after use."
"Apache Kafka on Confluent Cloud is critical infrastructure for us; without it, our infrastructure costs would increase significantly, potentially amounting to hundreds of thousands of dollars each year, and its real-time capabilities accelerate speed to value and enable new use cases, providing significant business value."
"The product's installation phase is pretty straightforward for us since we know how to use 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."
"Some of the best features with Apache Kafka on Confluent Cloud are streaming and event capabilities, which are important due to scalability and resiliency."
"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."
"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."
"Coralogix has positively impacted my organization by providing a centralized console to monitor the dashboard, giving me rich flexibility to see different sorts of data that is spread across the logs, metrics, or traces, which are the typical pillars of the observability tool."
"A non-tech person can easily get used to it."
"The solution offers very good convenience filtering."
"The initial setup is straightforward."
"The solution is easy to use and to start with."
"The overall stability and reliability of Coralogix are excellent, and I rarely encounter issues."
"The best feature of this solution allows us to correlate logs, metrics and traces."
"Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams."
 

Cons

"The clustering is a little hard for juniors and clients. It's suitable for senior engineers, but the configuration and clustering are very hard for juniors."
"There are some premium connectors, for example, available in Confluent, which you cannot access in the marketplace, so there are some limitations."
"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."
"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."
"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 solution is expensive."
"In terms of documentation, I think there can be more user-friendly documentation that stresses more on day-to-day issues."
"The customizable dashboards haven't really helped with my company's efficiency at all, and I think there's room for improvement."
"The user interface could be more intuitive and explanatory."
"The user interface is not intuitive, especially when first onboarding, and improvements could be made here."
"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions. The increasing volume of data and the resulting bandwidth charges are concerns."
"The features we were missing in the past were related to the way we see our metrics and aggregate our data."
"Maybe they could make it more user-friendly."
"The documentation of the tool could be improved"
 

Pricing and Cost Advice

"I consider that the product's price falls under the middle range category."
"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."
"We are paying roughly $5,000 a month."
"Currently, we are at a very minimal cost, which is around $400 per month since we have reduced our usage. Initially, we were at $900 per month."
"The platform has a reasonable cost. I rate the pricing a three out of ten."
"The cost of the solution is per volume of data ingested."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
8%
Comms Service Provider
6%
Insurance Company
5%
Financial Services Firm
10%
Computer Software Company
10%
Manufacturing Company
8%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise3
Large Enterprise8
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise5
 

Questions from the Community

What needs improvement with Apache Kafka on Confluent Cloud?
I think Apache Kafka on Confluent Cloud can be improved by probably working more around Confluent or the tool. In my opinion, it should utilize the response structures in a better way or be able to...
What is your primary use case for Apache Kafka on Confluent Cloud?
I have used Apache Kafka on Confluent Cloud for one of my projects with regard to log monitoring. My main use case for Apache Kafka on Confluent Cloud in that project was mainly streaming of the lo...
What advice do you have for others considering Apache Kafka on Confluent Cloud?
My advice to others looking into using Apache Kafka on Confluent Cloud is that it is easier and has a low learning curve. If there is any use case regarding streaming, I would suggest starting off ...
What do you like most about Coralogix?
Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams.
What is your experience regarding pricing and costs for Coralogix?
To monitor and manage costs associated with Coralogix, I analyze my trend, looking at how the data is being ingested. Generally, it is charged based on what we store, and therefore there are certai...
What needs improvement with Coralogix?
I think Coralogix can be improved with flexible dashboards. Creating specific views, such as saving a dev environment as a separate view rather than adding filters every time, would be great.
 

Overview

 

Sample Customers

Information Not Available
Payoneer, AGS, Monday.com, Capgemini
Find out what your peers are saying about Apache Kafka on Confluent Cloud vs. Coralogix and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.