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Apache Kafka vs Starburst Enterprise 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
8th
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
89
Ranking in other categories
No ranking in other categories
Starburst Enterprise
Ranking in Streaming Analytics
16th
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
Data Science Platforms (13th)
 

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 Starburst Enterprise is 3.7%, up from 2.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka3.7%
Starburst Enterprise3.7%
Other92.6%
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…
KamleshPant - PeerSpot reviewer
Connects to any data source from any region and offers unified access
There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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 stream processing is a very valuable aspect of the solution for us."
"The valuable features are the group community and support."
"Kafka can process messages in real-time, making it useful for applications that require near-instantaneous processing."
"The open-source version is relatively straightforward to set up and only takes a few minutes."
"Apache Kafka is an open-source solution that can be used for messaging or event processing."
"The most valuable feature is the messaging function and reliability."
"I appreciate that Apache Kafka is fast and secure thanks to implementing it with AWS, allowing me to secure it on a high level."
"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."
"It's very scalable, fast performing, and supports many catalogs."
 

Cons

"The solution could always add a few more features to enhance its usage."
"I would like to see monitoring service tools."
"We haven't seen a return on investment with Apache Kafka. It's used for a specific use case rather than cost reduction."
"The UI used to access Kafka topics can be further improved."
"For the original Kafka, there is room for improvement in terms of latency spikes and resource consumption. It consumes a lot of memory."
"While the solution scales well and easily, you need to understand your future needs and prep for the peaks."
"The price for the enterprise version is quite high. It would be better to have a lower price."
"I would like to see an improvement in authentication management."
"There should be support for REST API data sources to access data from the web."
"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."
 

Pricing and Cost Advice

"It's a premium product, so it is not price-effective for us."
"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."
"I would not subscribe to the Confluent platform, but rather stay on the free open source version. The extra cost wasn't justified."
"Apache Kafka has an open-source pricing."
"Apache Kafka is an open-source solution."
"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."
"Licensing issues are not applicable. Apache licensing makes it simple with almost zero cost for the software itself."
"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."
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Top Industries

By visitors reading reviews
Financial Services Firm
25%
Computer Software Company
12%
Manufacturing Company
8%
Retailer
5%
Financial Services Firm
41%
Computer Software Company
8%
Government
4%
Retailer
4%
 

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.
What is your experience regarding pricing and costs for Starburst Enterprise?
I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...
What needs improvement with Starburst Enterprise?
There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML ...
What is your primary use case for Starburst Enterprise?
We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...
 

Overview

 

Sample Customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest
Information Not Available
Find out what your peers are saying about Apache Kafka vs. Starburst Enterprise and other solutions. Updated: September 2025.
869,202 professionals have used our research since 2012.