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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 February 2026, in the Streaming Analytics category, the mindshare of Apache Kafka is 4.0%, up from 2.3% 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 Kafka4.0%
SAS Event Stream Processing0.9%
Other95.1%
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

"The convenience in setting up after major problems like data center blackouts is a notable feature."
"The most valuable feature is the messaging function and reliability."
"Resiliency is great and also the fact that it handles different data formats."
"There are numerous possibilities that can be explored. While it may be challenging to fully comprehend the potential advantages, one key aspect is the ability to establish a proper sequence of events rather than simply dealing with a jumbled group of occurrences. These events possess their own timestamps, even if they were not initially provided with one, and are arranged in a chronological order that allows for a clear understanding of the progression of the events."
"A great streaming platform."
"With Kafka, events and streaming are persistent, and multiple subscribers can consume the data. This is an advantage of Kafka compared to simple queue-based solutions."
"The stream processing is a very valuable aspect of the solution for us."
"As a software developer, I have found Apache Kafka's support to be the most valuable...The solution is easy to integrate with any of our systems."
"The solution is beneficial on an enterprise level."
 

Cons

"Too much dependency on the zookeeper and leader selection is still the bottleneck for Kafka implementation."
"Lacks elasticity and the ability to scale down."
"In the data sharing space, the performance of Apache Kafka could be improved. The performance angle is critical, and while it works in milliseconds, the goal is to move towards microseconds."
"Kafka has a lot of monitors, but sometimes it's most important to just have a simple monitor."
"Observability could be improved."
"In the data sharing space, the performance of Apache Kafka could be improved."
"The management tool could be improved."
"Maintaining and configuring Apache Kafka can be challenging, especially when you want to fine-tune its behavior."
"The persistence could be better."
 

Pricing and Cost Advice

"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."
"It is approximately $600,000 USD."
"Apache Kafka is an open-source solution and there are no fees, but there are fees associated with confluence, which are based on subscription."
"I would not subscribe to the Confluent platform, but rather stay on the free open source version. The extra cost wasn't justified."
"Kafka is an open-source solution, so there are no licensing costs."
"It's a bit cheaper compared to other Q applications."
"The cost can vary depending on the provider and the specific flavor or version you use. I'm not very knowledgeable about the pricing details."
"I was using the product's free version."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
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 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 needs improvement with Apache Kafka?
The long-term data storage feature in Apache Kafka depends on the setting, but I believe the maximum duration is seven days.
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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), Apache and others in Streaming Analytics. Updated: January 2026.
881,707 professionals have used our research since 2012.