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Apache Kafka vs IBM Event Streams 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
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
88
Ranking in other categories
Streaming Analytics (8th)
IBM Event Streams
Average Rating
8.4
Reviews Sentiment
7.8
Number of Reviews
3
Ranking in other categories
Message Queue (MQ) Software (10th)
 

Mindshare comparison

Apache Kafka and IBM Event Streams aren’t in the same category and serve different purposes. Apache Kafka is designed for Streaming Analytics and holds a mindshare of 3.0%, up 1.9% compared to last year.
IBM Event Streams, on the other hand, focuses on Message Queue (MQ) Software, holds 1.0% mindshare, up 0.9% since last year.
Streaming Analytics
Message Queue (MQ) Software
 

Featured Reviews

Snehasish Das - PeerSpot reviewer
Data streaming transforms real-time data movement with impressive scalability
I worked with Apache Kafka for customers in the financial industry and OTT platforms. They use Kafka particularly for data streaming. Companies offering movie and entertainment as a service, similar to Netflix, use Kafka Apache Kafka offers unique data streaming. It allows the use of data in…
Ismail El-Dahshan - PeerSpot reviewer
Easy to set up with good support and good routing scenarios
The triggering and the events that they have triggered as well as the route of the message according to the events are very useful. The triggering scenarios and routing scenarios are all good. It's a very useful solution for financial institutions. The initial setup is pretty straightforward. The stability has been good. I've found the product to be scalable. Technical support is responsive.

Quotes from Members

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

Pros

"The valuable features are the group community and support."
"Overall, I rate Apache Kafka as nine out of ten for its scalability and stability."
"Kafka, as compared with other messaging system options, is great for large scale message processing applications. It offers high throughput with built-in fault-tolerance and replication."
"Kafka is scalable. It can manage a high volume of data from many sources."
"The most valuable feature is the performance."
"A great streaming platform."
"I like the performance and reliability of Kafka. I needed a data streaming buffer that could handle thousands of messages per second with at least one processing point for an analytics pipeline. Kafka fits this requirement very well."
"It is a useful way to maintain messages and to manage offset from our consumers."
"The system efficiently processes and calculates the data flow within the cluster using DLP functionality."
"The stability has been good."
"I'm an administrator, and what I like most is the interface, the security, and the storage."
 

Cons

"Lacks elasticity and the ability to scale down."
"Kafka is a nightmare to administer."
"One complexity that I faced with the tool stems from the fact that since it is not kind of a stand-alone application, it won't integrate with native cloud, like AWS or Azure."
"We cannot apply all of our security requirements because it is hard to upload them."
"If the graphical user interface was easier for the Kafka administration it would be much better. Right now, you need to use the program with the command-line interface. If the graphical user interface was easier, it could be a better product."
"In the data sharing space, the performance of Apache Kafka could be improved."
"The solution should be easier to manage. It needs to improve its visualization feature in the next release."
"Apache Kafka could improve data loss and compatibility with Spark."
"It would be helpful if they could help us explain why they, as in, the customers, should use the product and the overall benefits."
"The product's interface needs improvement."
"In the next release, I would like to see the GUI allow you to configure the security section."
 

Pricing and Cost Advice

"It's a premium product, so it is not price-effective for us."
"The solution is free, it is open-source."
"Apache Kafka is an open-source solution and there are no fees, but there are fees associated with confluence, which are based on subscription."
"It is open source software."
"Apache Kafka has an open-source pricing."
"Kafka is open-source and it is cheaper than any other product."
"Apache Kafka is free."
"The solution is open source; it's free to use."
"The platform is averagely priced."
"The pricing needs to be improved."
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Top Industries

By visitors reading reviews
Financial Services Firm
29%
Computer Software Company
12%
Manufacturing Company
7%
Retailer
6%
Financial Services Firm
28%
Computer Software Company
13%
Retailer
10%
Real Estate/Law Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What are the differences between Apache Kafka and IBM MQ?
Apache Kafka is open source and can be used for free. It has very good log management and has a way to store the data used for analytics. Apache Kafka is very good if you have a high number of user...
What do you like most about Apache Kafka?
Apache Kafka is an open-source solution that can be used for messaging or event processing.
What is your experience regarding pricing and costs for Apache Kafka?
Its pricing is reasonable. It's not always about cost, but about meeting specific needs.
What do you like most about IBM Event Streams?
The system efficiently processes and calculates the data flow within the cluster using DLP functionality.
What is your experience regarding pricing and costs for IBM Event Streams?
The platform is averagely priced. I rate the pricing a six out of ten.
What needs improvement with IBM Event Streams?
The product's interface needs improvement. Additionally, there could be a management console to create and manage clusters.
 

Overview

 

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest
American Airlines, UBank, Bitly, Eurobits, Active International, Bison, Contextor, Constance Hotels, Resorts & Golf, Creval, Deloitte, ExxonMobil, FaceMe, FacePhi, Fitzsoft, Fuga Technologies, Guardio, Honeywell, Japanese airline, Jenzabar, KONE
Find out what your peers are saying about Apache Kafka vs. IBM Event Streams and other solutions. Updated: May 2024.
856,873 professionals have used our research since 2012.