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Apache Pulsar vs Starburst Galaxy 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 Pulsar
Ranking in Streaming Analytics
20th
Average Rating
8.0
Reviews Sentiment
6.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Starburst Galaxy
Ranking in Streaming Analytics
12th
Average Rating
9.8
Reviews Sentiment
1.0
Number of Reviews
9
Ranking in other categories
Data Science Platforms (9th)
 

Mindshare comparison

As of April 2026, in the Streaming Analytics category, the mindshare of Apache Pulsar is 2.8%, up from 2.0% compared to the previous year. The mindshare of Starburst Galaxy is 1.7%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Starburst Galaxy1.7%
Apache Pulsar2.8%
Other95.5%
Streaming Analytics
 

Featured Reviews

it_user1087029 - PeerSpot reviewer
Solution Architect at Vlaanderen connect.
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.
reviewer2750097 - PeerSpot reviewer
VP, Business Intelligence at a outsourcing company with 501-1,000 employees
Unified data access improves analytics and simplifies complex processes
I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs. I also want support for more connectors such as Kinesis and Firehose, support for more file types such as Avro and JSON, and object storage message queue integration for object storage integrations. A single view of query execution and optimization details, rather than needing to toggle between the Galaxy and Trino UI, would be helpful. Additionally, enhanced control over account and environment variables that would be available in the Enterprise edition would be beneficial.

Quotes from Members

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

Pros

"The solution operates as a classic message broker but also as a streaming platform."
"The solution operates as a classic message broker but also as a streaming platform."
"I am now able to answer questions in a couple of minutes that would otherwise take hours or days of time for my data engineering teams."
"Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
"Starburst Galaxy serves as our primary SQL-based data processing engine, a strategic decision driven by its seamless integration with our AWS cloud infrastructure and its ability to deliver high performance with low-latency responses."
"I use Starburst as a cost-efficient hosted option for Trino for data integration and ad-hoc analysis across a broad range of data sources."
"Starburst Galaxy has significantly improved our data architecture flexibility and performance management by solving cross-database query challenges and enabling us to utilize iceberg tables externally across our entire data ecosystem."
"The most fundamental feature is the query engine, which is much faster than any of the competitors; Starburst is able to finish most queries within 10 seconds, which is especially important for many non-technical employees."
"Starburst has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."
"Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
 

Cons

"Documentation is poor because much of it is in Chinese with no English translation."
"Documentation is poor because much of it is in Chinese with no English translation."
"Cluster startup time can be slow, sometimes taking over a minute."
"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."
"Cluster startup time is another pain point, typically 3 to 5 minutes, which is not the worst with proper planning but can be annoying for ad-hoc work."
"Multi-tenancy could be improved. In order to have multiple environments for SSO, we maintain multiple tenants that are connected to different AWS accounts via the Marketplace."
"The most persistent issue is the cluster spin-up time."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Comms Service Provider
9%
Government
9%
Insurance Company
7%
Financial Services Firm
24%
Computer Software Company
14%
University
8%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise1
 

Questions from the Community

Ask a question
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What is your experience regarding pricing and costs for Starburst Galaxy?
I recommend experimenting with different cluster sizes to determine what works best for your particular use case.
What needs improvement with Starburst Galaxy?
Multi-tenancy could be improved. In order to have multiple environments for SSO, we maintain multiple tenants that are connected to different AWS accounts via the Marketplace. On the AWS side this ...
What is your primary use case for Starburst Galaxy?
I use the solution for processing large simulation datasets into aggregated datasets that can either be used for real-time data analysis or stored for later analysis.
 

Overview

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: March 2026.
885,789 professionals have used our research since 2012.