Apache Kafka on Confluent Cloud vs JFrog DevOps Cloud Platform comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache Kafka on Confluent C...
Ranking in AWS Marketplace
4th
Average Rating
8.4
Number of Reviews
5
Ranking in other categories
No ranking in other categories
JFrog DevOps Cloud Platform
Ranking in AWS Marketplace
31st
Average Rating
7.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2024, in the AWS Marketplace category, the mindshare of Apache Kafka on Confluent Cloud is 2.2%, up from 1.9% compared to the previous year. The mindshare of JFrog DevOps Cloud Platform is 0.9%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AWS Marketplace
Unique Categories:
No other categories found
No other categories found
 

Featured Reviews

CR
Jan 26, 2024
Helps us manage transactions effectively and integrates seamlessly with our data analysis tools
In terms of configuring the product, specifically Confluent, understanding the design and configuring values for various parameters is something only I am familiar with. The initial setup, including the initial Non-Disclosure Agreement (NDA) and progress in implementation, is quite difficult. We primarily use on-premises Kafka for high-transaction scenarios. If something crashes there, we handle data processing manually. It might not be the most efficient, but we haven't considered it a major concern. For other use cases, we also prefer on-premises. The implementation took us one year. It involved configuring the platform over a year. The time required for configuring or implementing use cases varies; some take longer, while others might also take up to a year.
Balasubramani Murugesan - PeerSpot reviewer
May 22, 2024
Has replication delays and documentation issues, but provides a professional technical support team
Our locations are in different environments, so the remote server takes time to catch up, causing replication delays. The engineering team suggested that this issue would be resolved, but I'm not sure if it has been addressed yet. This is more of a feature enhancement that we suggested. The…

Quotes from Members

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

Pros

"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."
"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."
"In case of huge transactions on the web or mobile apps, it helps you capture real-time data and analyze it."
"They have a professional service team that works alongside their engineering and performance teams."
 

Cons

"For the original Kafka, there is room for improvement in terms of latency spikes and resource consumption. It consumes a lot of memory."
"There could be an in-built feature for data analysis."
"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 administration port could be more extensive."
"Our locations are in different environments, so the remote server takes time to catch up, causing replication delays. The engineering team suggested that this issue would be resolved, but I'm not sure if it has been addressed yet. This is more of a feature enhancement that we suggested."
 

Pricing and Cost Advice

"It's quite affordable considering the value it provides."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Healthcare Company
9%
Government
9%
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...
What needs improvement with Apache Kafka on Confluent Cloud?
The administration port could be more extensive. Additionally, managing the states of certain events could be made easier, perhaps with automatic rollback instead of having to program it manually.
What is your primary use case for Apache Kafka on Confluent Cloud?
Whenever you need to handle a huge load of real-time data processing, Kafka is useful. We currently use it for an output management system for insurance, where the system receives data in a fixed a...
What needs improvement with JFrog DevOps Cloud Platform?
Our locations are in different environments, so the remote server takes time to catch up, causing replication delays. The engineering team suggested that this issue would be resolved, but I'm not s...
 

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Overview

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