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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
6.9
Number of Reviews
89
Ranking in other categories
No ranking in other categories
SAS Event Stream Processing
Ranking in Streaming Analytics
28th
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 September 2025, in the Streaming Analytics category, the mindshare of Apache Kafka is 3.6%, up from 2.0% compared to the previous year. The mindshare of SAS Event Stream Processing is 0.6%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka3.6%
SAS Event Stream Processing0.6%
Other95.8%
Streaming Analytics
 

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…
Roi Jason Buela - PeerSpot reviewer
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 makes data streaming asynchronous and decouples the reliance of events on consumers."
"Apache Kafka is particularly valuable for stream data processing, handling transactions, managing high levels of transactions, and orchestrating stream mode data."
"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."
"When comparing it with other messaging and integration platforms, this is one of the best rated."
"Good horizontal scaling and design."
"The most valuable feature is the performance."
"Excellent speeds for publishing messages faster."
"Apache Kafka is effective when dealing with large volumes of data flowing at high speeds, requiring real-time processing."
"The solution is beneficial on an enterprise level."
 

Cons

"For personal preferences, since we use Managed Kafka in AWS, I would appreciate having some kind of UI integrated into Apache Kafka for connecting to it because using code to connect it is basic, but we can use a UI."
"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."
"Maintaining and configuring Apache Kafka can be challenging, especially when you want to fine-tune its behavior."
"We cannot apply all of our security requirements because it is hard to upload them."
"We haven't seen a return on investment with Apache Kafka. It's used for a specific use case rather than cost reduction."
"Apache Kafka can improve by adding a feature out of the box which allows it to deliver only one message."
"The initial setup and deployment could be less complex."
"The persistence could be better."
 

Pricing and Cost Advice

"Apache Kafka is open-source and can be used free of charge."
"This is an open-source solution and is free to use."
"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 and there are no fees, but there are fees associated with confluence, which are based on subscription."
"This is an open-source version."
"The solution is open source."
"We are using the free version of Apache Kafka."
"Kafka is more reasonably priced than IBM MQ."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
12%
Manufacturing Company
8%
Retailer
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business32
Midsize Enterprise18
Large Enterprise47
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), Confluent and others in Streaming Analytics. Updated: September 2025.
868,229 professionals have used our research since 2012.