Try our new research platform with insights from 80,000+ expert users

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

"The most valuable features of the solution revolve around areas like the latency part, where the tool offers very little latency and the sequencing part."
"It eases our current data flow and framework."
"The most valuable feature of Apache Kafka is its versatility. It can solve many use cases or can be a part of many use cases. Its fundamental value of it is in the real-time processing capability."
"It is easy to configure."
"The most valuable feature of Kafka is the Kafka Streams client."
"Apache Kafka has good integration capabilities and has plenty of adapters in its ecosystem if you want to build something. There are adapters for many platforms, such as Java, Azure, and Microsoft's ecosystem. Other solutions, such as Pulsar have fewer adapters available."
"Overall, I rate Apache Kafka as nine out of ten for its scalability and stability."
"Deployment is speedy."
"The solution is beneficial on an enterprise level."
 

Cons

"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."
"We struggled a bit with the built-in data transformations because it was a challenge to get them up and running the way we wanted."
"Prioritization of messages in Apache Kafka could improve."
"Kafka's interface could also use some work. Some of our products are in C, and we don't have any libraries to use with C. From an interface perspective, we had a library from the readies. And we are streaming some of the products we built to readies. That is one of the requirements. It would be good to have those libraries available in a future release for our C++ clients or public libraries, so we can include them in our product and build on that."
"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."
"The interface has room for improvement, and there is a steep learning curve for Hadoop integration. It was a struggle learning to send from Hadoop to Kafka. In future releases, I'd like to see improvements in ETL functionality and Hadoop integration."
"The solution's initial setup process was complex."
"The interface of Apache Kafka could be significantly better."
"The persistence could be better."
 

Pricing and Cost Advice

"Kafka is open-source and it is cheaper than any other product."
"Kafka is more reasonably priced than IBM MQ."
"It's a bit cheaper compared to other Q applications."
"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."
"This is an open-source solution and is free to use."
"This is an open-source version."
"Apache Kafka is an open-source solution."
"Apache Kafka is an open-source solution."
Information not available
report
Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
881,082 professionals have used our research since 2012.
 

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.
Ask a question
Earn 20 points
 

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.