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Apache Kafka vs SAS Event Stream Processing 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
Ranking in Streaming Analytics
7th
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
90
Ranking in other categories
No ranking in other categories
SAS Event Stream Processing
Ranking in Streaming Analytics
25th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Apache Kafka is 3.8%, up from 2.2% compared to the previous year. The mindshare of SAS Event Stream Processing is 0.9%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka3.8%
SAS Event Stream Processing0.9%
Other95.3%
Streaming Analytics
 

Featured Reviews

Bruno da Silva - PeerSpot reviewer
Senior Manager at Timestamp, SA
Have worked closely with the team to deploy streaming and transaction pipelines in a flexible cloud environment
The interface of Apache Kafka could be significantly better. I started working with Apache Kafka from its early days, and I have seen many improvements. The back office functionality could be enhanced. Scaling up continues to be a challenge, though it is much easier now than it was in the beginning.
Roi Jason Buela - PeerSpot reviewer
Lead Technical Consultant at Thakral One
A solution with useful windowing features and great for operations and marketing
The persistence could be better. Although ESP is designed for in-memory processing, it would be better if the solution is enhanced or improved on the persistence of the data that is kept in the memory. For example, if one server goes down and the information is stored in the memory, it is lost. Therefore, the persistence needs to be improved so that if there are more cases where the server is down, the information and data can still be intact.

Quotes from Members

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

Pros

"Kafka provides us with a way to store the data used for analytics. That's the big selling point. There's very good log management."
"The most valuable feature is the messaging function and reliability."
"valuable features relate to microservices architecture and working on KStream and KSQL DB as a microservices event bus."
"The most valuable feature is the support for a high volume of data."
"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."
"The open-source version is relatively straightforward to set up and only takes a few minutes."
"Kafka makes data streaming asynchronous and decouples the reliance of events on consumers."
"Robust and delivers messages quickly."
"The solution is beneficial on an enterprise level."
 

Cons

"I suggest using cloud services because the solution is expensive if you are using it on-premises."
"would like to see real-time event-based consumption of messages rather than the traditional way through a loop. The traditional messaging system works by listing and looping with a small wait to check to see what the messages are. A push system is where you have something that is ready to receive a message and when the message comes in and hits the partition, it goes straight to the consumer versus the consumer having to pull. I believe this consumer approach is something they are working on and may come in an upcoming release. However, that is message consumption versus message listening."
"The management overhead is more compared to the messaging system. There are challenges here and there. Like for long usage, it requires restarts and nodes from time to time."
"In Apache Kafka, it is currently difficult to create a consumer."
"The GUI tools for monitoring and support are still very basic and not very rich. There is no help in determining a shard key for performance."
"Some vendors don't offer extra features for monitoring."
"The UI is based on command line. It would be helpful if they could come up with a simpler user interface."
"Kafka is complex and there is a little bit of a learning curve."
"The persistence could be better."
 

Pricing and Cost Advice

"The solution is free, it is open-source."
"Apache Kafka is an open-sourced solution. There are fees if you want the support, and I would recommend it for enterprises. There are annual subscriptions available."
"Apache Kafka is an open-source solution."
"I rate Apache Kafka's pricing a five on a scale of one to ten, where one is cheap and ten is expensive. There are no additional costs apart from the licensing fees for Apache Kafka."
"The solution is open source; it's free to use."
"I was using the product's free version."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Computer Software Company
11%
Manufacturing Company
9%
Retailer
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business32
Midsize Enterprise18
Large Enterprise49
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.
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Overview

 

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest
Honda, HSBC, Lufthansa, Nestle, 89Degrees.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: January 2026.
881,082 professionals have used our research since 2012.