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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
3rd
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
92
Ranking in other categories
No ranking in other categories
Starburst Enterprise
Ranking in Streaming Analytics
19th
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
Data Science Platforms (16th)
 

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 Starburst Enterprise is 2.3%, down from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Apache Kafka3.8%
Starburst Enterprise2.3%
Other93.9%
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.
KamleshPant - PeerSpot reviewer
Senior Software Architect at USEReady
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 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."
"The most valuable features to me are replication, partitioning and easy integration with Apache Spark, which we use quite a bit for distributed processing."
"We get amazing throughput. We don't get any delay."
"The publisher-subscriber pattern and low latency are also essential features that greatly piqued my interest."
"Kafka is scalable. It can manage a high volume of data from many sources."
"The stream processing is a very valuable aspect of the solution for us."
"The most valuable feature is the speed at which the solution can be deployed."
"The solution is stable, and the most fantastic thing about it is its throughput."
"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 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)."
"The UI used to access Kafka topics can be further improved."
"The user interface is one weakness. Sometimes, our data isn't as accessible as we'd like. It takes a lot of work to retrieve the data and the index."
"Kafka has a lot of monitors, but sometimes it's most important to just have a simple monitor."
"I would like them to reduce the learning curve around the creation of brokers and topics. They also need to improve on the concept of the partitions."
"It needs a separate cluster and a separate administrator to manage the Kafka cluster, adding an extra cost."
"The initial setup is simple, but the ongoing management becomes challenging."
"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."
"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

"Running a Kafka cluster can be expensive, especially if you need to scale it up to handle large amounts of data."
"Apache Kafka is open-source and can be used free of charge."
"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."
"It's a bit cheaper compared to other Q applications."
"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."
"It's quite affordable considering the value it provides."
"The price of Apache Kafka is good."
"Apache Kafka is an open-source solution."
"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
17%
Outsourcing Company
12%
Manufacturing Company
10%
Construction Company
8%
Financial Services Firm
34%
Computer Software Company
7%
Manufacturing Company
6%
Construction Company
5%
 

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...
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...
What advice do you have for others considering Starburst Enterprise?
Starburst requires a heavy investment in infrastructure; it needs heavy computing and storage. If your use case doesn't involve heavy processing or storage, then Starburst might not be the solution...
 

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: August 2026.
909,725 professionals have used our research since 2012.