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Dremio vs Starburst Galaxy comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Feb 15, 2026

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

Dremio
Ranking in Data Science Platforms
9th
Average Rating
8.4
Reviews Sentiment
6.5
Number of Reviews
14
Ranking in other categories
Cloud Data Warehouse (10th)
Starburst Galaxy
Ranking in Data Science Platforms
7th
Average Rating
9.4
Reviews Sentiment
2.6
Number of Reviews
12
Ranking in other categories
Streaming Analytics (9th)
 

Mindshare comparison

As of November 2026, in the Data Science Platforms category, the mindshare of Dremio is 2.0%, down from 2.9% compared to the previous year. The mindshare of Starburst Galaxy is 1.5%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Starburst Galaxy1.5%
Dremio2.0%
Other96.5%
Data Science Platforms
 

Featured Reviews

Corrr Moray - PeerSpot reviewer
SR BI developer at BRQ Digital Solutions
Has simplified complex data integration workflows and supported consistent reporting across multiple sources
We also have a close relationship with the team that does the Dremio maintenance for the database, like upgrading the versions and they know about some specific problems we had in the past, such as a memory leak. We had a memory leak on some versions, which sometimes stopped the service. Since we are using Dremio installed like a server, not a SaaS solution, many times we need to stop and restart the service to clear all the cache and all that, and this is the thing I should add. I see that many times the new versions of Dremio have not fixed old bugs, and in some new versions, old problems that were previously fixed come back again, so I think the upgrade part could use improvement. I remember using some features in the past, like pivot tables, which proved to be really difficult, but I know this is a fault also for other vendors. Pivoting, transposing, and unpivoting are often not so good. CTEs also many times prove to be not so good, so I think these two main items could be improved significantly if they standardize them.
Pedromachado Ventura - PeerSpot reviewer
Data Analyst at a financial services firm with 5,001-10,000 employees
Unified SQL layer has streamlined access to distributed historical data for analytics and reporting
One area that I think could be improved is the experience when performance issues occur. When a query is slow, it is not always immediately obvious to me whether the bottleneck comes from Starburst Galaxy itself, the underlying data source, the query design, or the reporting tool. Better visibility into query performance and easier diagnostics for non-administrators would be useful. Another potential improvement would be enhancing the experience with BI tools to make it more seamless. I work a lot with Power BI, and when you are working with larger data sets, performance can sometimes depend on several different layers. Having more visibility into what is happening between the BI tool, Starburst Galaxy, and the underlying source would be helpful. I also think onboarding could be a little more accessible for analysts. There is good technical documentation, but sometimes I just need to understand the best way to approach a common use case without diving too deep into the platform architecture. The main improvement would be troubleshooting. I have not used the AI capabilities extensively, so I cannot give a detailed assessment. I am not sure if my organization has the full capabilities of Starburst Galaxy, but I think adding AI on top of the data layer is interesting, especially if it can help users discover data, understand data sets, and interact with them more naturally. For governance and security, one of the strengths of Starburst Galaxy is that you can centralize access to data while still controlling what different users are allowed to see. Role-based access, fine-grained permissions, and data masking are important because giving people easier access to data should not mean giving everyone access to everything. I think that is even more important than any AI capabilities that are introduced. If you do introduce AI, I think it should respect exactly the same data permissions and governance rules as the user that is accessing the data.

Quotes from Members

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

Pros

"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"We primarily use Dremio to create a data framework and a data queue."
"It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS."
"Overall, you can rate it as eight out of ten."
"Reflections pre-calculate results which are then just delivered instantly, meaning you do not need to wait to run a query for a longer time on huge amounts of data, and the user gets very quick answers."
"Dremio allows querying the files I have on my block storage or object storage."
"The primary value I find in Dremio is that this tool is mainly used to query data that are split amongst several sources and to virtualize those sources so that the end user faces it as a single source of truth of data."
"The native error interface has been most valuable."
"The main positive impact Starburst Galaxy has made is making data more accessible for analytics and reporting."
"Starburst Galaxy is becoming a cornerstone of our data platform, empowering us to make smarter and faster decisions across the organization."
"Starburst on Trino, combined with our SQL-native data transformation tool SQLMesh, has delivered anywhere from a two to five times improvement in compute performance across our transformation DAG."
"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."
"Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
"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 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."
"Starburst Galaxy has positively impacted my organization by allowing us to rethink the strategy for data and architect data differently; instead of having multiple data marts and siloed data marts, we have a unified vision, and that is how it is changing."
 

Cons

"Dremio could be improved by making it easier for data cataloging, especially when working with open table formats, as you have to choose a data format and then go into it."
"It shows errors sometimes."
"We had a memory leak on some versions, which sometimes stopped the service."
"They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today."
"One area where Dremio can be improved is the lack of tooling or functionalities for importing data in a pipeline way, as it is not an ETL or ELT component."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"We had some crash issues concerning part of the engine caused by one query that made the engine crash."
"The community version lacks information or documentation."
"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."
"The most persistent issue is the cluster spin-up time."
"I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs."
"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."
"I think there are areas of improvement with respect to AI adaptability, and also in general, the amount of connectors working with other tools are areas where it can be expanded."
"There is still room for improved usability and diagnostics, especially for users who are not platform specialists."
"Cluster startup time can be slow, sometimes taking over a minute."
"As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options."
 

Pricing and Cost Advice

"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
"Dremio is less costly competitively to Snowflake or any other tool."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Outsourcing Company
8%
Comms Service Provider
8%
Manufacturing Company
6%
Financial Services Firm
29%
Computer Software Company
10%
Manufacturing Company
6%
Construction Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise6
Large Enterprise5
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise4
 

Questions from the Community

What is your experience regarding pricing and costs for Dremio?
I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.
What needs improvement with Dremio?
I think Dremio can be improved to query faster than multiple sources and big data lakehouses. The community version could be updated for new data catalog connections. I think the documentation is s...
What is your primary use case for Dremio?
I have been using Dremio to select multiple data sources, retrieve multiple data sources, and create and maintain Iceberg tables for the data lakehouse. My main use case for Dremio is to actively c...
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?
One area that I think could be improved is the experience when performance issues occur. When a query is slow, it is not always immediately obvious to me whether the bottleneck comes from Starburst...
What is your primary use case for Starburst Galaxy?
I have mainly used Starburst Galaxy as a query and access layer for analytical data, as my current work involves dealing with data stored across different platforms, including Hive and SingleStore....
 

Comparisons

 

Also Known As

Dremio AWS - BYOL
No data available
 

Overview

 

Sample Customers

UBS, TransUnion, Quantium, Daimler, OVH
Information Not Available
Find out what your peers are saying about Dremio vs. Starburst Galaxy and other solutions. Updated: September 2026.
920,929 professionals have used our research since 2012.