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Apache Kafka vs IBM Streams comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

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
3rd
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
No ranking in other categories
IBM Streams
Ranking in Streaming Analytics
24th
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Streaming Analytics category, the mindshare of Apache Kafka is 3.8%, up from 3.5% compared to the previous year. The mindshare of IBM Streams is 2.2%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Apache Kafka3.8%
IBM Streams2.2%
Other94.0%
Streaming Analytics
 

Featured Reviews

Amandeep Pawar - PeerSpot reviewer
Senior Engineer at Airy Software Technologies Private Limited
Event-driven architecture has improved asynchronous communication and supports high throughput
We can improve the high throughput because there are some limitations. We could add something to improve Apache Kafka. Based on my daily usage and analysis, there is a complex setup and management, which is one area requiring improvement. Apache Kafka does not have built-in message delay or scheduling capabilities. Apache Kafka cannot natively schedule messages. Limited message prioritization is also an area requiring improvement. Ordering is limited to a single partition. Large messages affect performance. Apache Kafka is optimized for many small to medium-sized messages, but large payloads increase network usage, increase disk usage, and slow down producers and consumers. I rate Apache Kafka eight out of ten instead of ten out of ten because operating an Apache Kafka cluster requires expertise in partitioning, application monitoring, and capacity planning. Self-managed deployment can become complex as the cluster grows. Pro-managed Apache Kafka services significantly reduce the operational overhead.
Ahmed_Emad - PeerSpot reviewer
Territory Sales Leader at Sumerge
A solution for data pipelines but has connector limitations
We have used Kafka for seven years. IBM streams gives you many OOTB features that can boost the time-to-market, especially when it comes to reporting and monitoring for example. Confluent is recognized as one of the leaders in this space and the main reason for this is related to the complete vision of the platform also the large number of connectors. This gives the edge and competitive advatnage.

Quotes from Members

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

Pros

"It just works and it's super fast."
"This is a system for email and other small devices, and there has been a relay of transactions continuously over the last two years it has been in production."
"The high availability is valuable. It is robust, and we can rely on it for a huge amount of data."
"We implemented the notification system between our components, and we found that Apache Kafka performs well in scalability, improving our organization because of the scalability and the comfort of a fail-safe or disaster recovery it provides."
"It has become dead simple to connect different application and services, saving a lot of development hours."
"One of the most valuable features I have found is Kafka Connect."
"The valuable features are the group community and support."
"The most valuable feature is the messaging function and reliability."
"As a result, the TELCO company was able to cut down the time it took to respond to customer needs and there were fewer complaints."
"The product has enabled us to create solutions to client problems that would have either been impossible or very expensive/difficult using other technologies."
"The OEM Solution (Excel-medical.com) running on top of IBM Streams provides real-time clinical algorithms that can give better insight into the patient's acuity, thus cutting off time to discharge patients and inversely making sure that sick patients don't get discharged until ready."
"Easy development and deployment, Java implementation features, and the real time analyser and alarm function are the most valuable features for us."
 

Cons

"There have been some challenges with monitoring Apache Kafka, as there are currently only a few production-grade solutions available, which are all under enterprise license and therefore not easily accessible. The speaker has not had access to any of these solutions and has instead relied on tools, such as Dynatrace, which do not provide sufficient insight into the Apache Kafka system. While there are other tools available, they do not offer the same level of real-time data as enterprise solutions."
"I suggest using cloud services because the solution is expensive if you are using it on-premises."
"Kafka's interface could also use some work."
"There is a lot of information available for the solution and it can be overwhelming to sort through."
"Confluent has improved aspects like documentation and cloud support, yet Kafka's reliance on older architectures like ZooKeeper in previous versions is a limitation."
"One improvement is in regards to the OS memory management."
"Managing Apache Kafka can be a challenge, but there are solutions. I used the newest release, as it seems they have removed Zookeeper, which should make it easier. Confluent provides a fully managed Kafka platform, in which the cluster does not need to be managed."
"Config management can be better. We are always trying to find the best configs, which is a challenge."
"We had some stability issues where we used embedded Zookeeper in production."
"The price and versatility of this product need to improve - it is not inexpensive."
"The development IDE sometimes crashes and freezes."
"I’d like to see a tool kit specifically targeted at incremental machine learning. It’s already great for scoring previously trained models, but dynamically updating models is currently more of a 'grow your own' kind of thing."
 

Pricing and Cost Advice

"The solution is free, it is open-source."
"When starting to look at a distributed message system, look for a cloud solution first. It is an easier entry point than an on-premises hardware solution."
"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."
"Licensing issues are not applicable. Apache licensing makes it simple with almost zero cost for the software itself."
"I was using the product's free version."
"We are using the free version of Apache Kafka."
"It is open source software."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Outsourcing Company
12%
Manufacturing Company
10%
Construction Company
8%
Government
20%
Financial Services Firm
15%
Construction Company
15%
Comms Service Provider
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business33
Midsize Enterprise20
Large Enterprise51
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?
From the AWS perspective, the price is on the higher side. However, if you go for Apache Kafka, it is low. From a price perspective, if you are asking about Apache Kafka, I would rate it a nine.
What needs improvement with Apache Kafka?
Apache Kafka is abundant with features which only an expert-level person will be able to manage due to the high volume and high concurrent expectations. Apache Kafka groups could introduce themes o...
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Comparisons

 

Also Known As

No data available
IBM InfoSphere Streams
 

Overview

 

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest
Globo TV, All England Lawn Tennis Club, CenterPoint Energy, Consolidated Communications Holdings, Darwin Ecosystem, Emory University Hospital, ICICI Securities, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Living Roads, Mobileum, Optibus, Southern Ontario Smart Computing Innovation Platform (SOSCIP), University of Alberta, University of Montana, University of Ontario Institute of Technology, Wimbledon 2015
Find out what your peers are saying about Apache Kafka vs. IBM Streams and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.