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Apache Kafka vs Apache Pulsar 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
8th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
89
Ranking in other categories
No ranking in other categories
Apache Pulsar
Ranking in Streaming Analytics
21st
Average Rating
8.0
Reviews Sentiment
6.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Streaming Analytics category, the mindshare of Apache Kafka is 3.7%, up from 2.0% compared to the previous year. The mindshare of Apache Pulsar is 2.3%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka3.7%
Apache Pulsar2.3%
Other94.0%
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…
it_user1087029 - PeerSpot reviewer
The solution can mimic other APIs without changing a line of code
The solution operates as a classic message broker but also as a streaming platform. It operates differently than a traditional streaming platform with storage and computing handled separately. It scales easier and better than Kafka which can be stubborn. You can even make it act like Kafka because it understands Kafka APIs. There are even companies that will sell you Kafka but underneath it is Apache Pulsar. The solution is very compatible because it can mimic other APIs without changing a line of code.

Quotes from Members

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

Pros

"The main advantage is increased reliability, particularly with regard to data and the speed with which messages are published to the other side."
"The valuable features are the group community and support."
"Kafka's most valuable feature is its user-friendliness."
"The ability to partition data on Kafka is valuable."
"Its availability is brilliant."
"Resiliency is great and also the fact that it handles different data formats."
"One of the most valuable features I have found is Kafka Connect."
"For example, when you want to send a message to inform all your clients about a new feature, you can publish that message to a single topic in Apache Kafka. This allows all clients subscribed to that topic to receive the message. On the other hand, if you need to send billing information to a specific customer, you can publish that message on a topic dedicated to that customer. This message can then be sent as an SMS to the customer, allowing them to view it on their mobile device."
"The solution operates as a classic message broker but also as a streaming platform."
 

Cons

"Config management can be better. We are always trying to find the best configs, which is a challenge."
"The solution could always add a few more features to enhance its usage."
"The repository isn't working very well. It's not user friendly."
"Kafka is complex and there is a little bit of a learning curve."
"I would like to see an improvement in authentication management."
"They need to have a proper portal to do everything because, at this moment, Kafka is lagging in this regard."
"I would like to see monitoring service tools."
"The product is good, but it needs implementation and on-going support. The whole cloud engagement model has made the adoption of Kafka better due to PaaS (Amazon Kinesis, a fully managed service by AWS)."
"Documentation is poor because much of it is in Chinese with no English translation."
 

Pricing and Cost Advice

"The solution is open source."
"It's a premium product, so it is not price-effective for us."
"Kafka is more reasonably priced than IBM MQ."
"The solution is free, it is open-source."
"The price for the enterprise version is quite high. For on-premise, there is an annual fee, which starts at 60,000 euros, but it is usually higher than 100,000 euros. The cost for a project including the subscription is usually between 100,000 to 200,000 euros. The cost also depends on the level of support. There are two different levels of support."
"Kafka is an open-source solution, so there are no licensing costs."
"The price of Apache Kafka is good."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Computer Software Company
12%
Manufacturing Company
9%
Retailer
5%
Computer Software Company
18%
Financial Services Firm
12%
Comms Service Provider
9%
Manufacturing Company
8%
 

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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Comparisons

 

Overview

 

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest
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Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Confluent and others in Streaming Analytics. Updated: September 2025.
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