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Darwin vs Dremio 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:
 

ROI

Sentiment score
6.2
Companies find Darwin efficient, preventing revenue loss and enhancing machine learning, with returns two to three times higher.
Sentiment score
4.0
Dremio offers cost savings and efficiency by reducing infrastructure needs and simplifying data source integration on data lakes.
Dremio surely saves time, reduces costs, and all those things because we don't have to worry so much about the infrastructure to make the different tools communicate.
SR BI developer at BRQ Digital Solutions
 

Customer Service

Sentiment score
8.4
Darwin's support is highly responsive and efficient, quickly resolving issues and providing valuable guidance, ensuring customer satisfaction.
Sentiment score
6.1
Dremio's customer service is highly praised for responsiveness, with Gold plan users enjoying positive interactions despite some limitations.
We contact the technical support at least weekly; currently, it's more or less daily because we face performance issues, crashes of queries sometimes, and we also need support for configuration of the query engines and so on.
Data Architect at a consultancy with 51-200 employees
I would rate customer support a ten out of ten.
We have had to reach out for customer support many times, and they respond, so they are pretty supportive about some long-term issues.
SR BI developer at BRQ Digital Solutions
 

Scalability Issues

Sentiment score
6.7
Darwin scales well with challenges on large datasets; plans for expansion need internal changes for wider departmental adoption.
Sentiment score
7.3
Dremio's scalability excels, with user-configurable auto-scaling on Kubernetes/Docker, meeting large-scale needs, but some features require licensing.
Dremio's scalability can handle growing data and user demands easily.
SR BI developer at BRQ Digital Solutions
Dremio's scalability depends on your hardware and your deployment.
Internally, if it's on Docker or Kubernetes, scalability will be built into the system.
Senior Software Architect at USEReady
 

Stability Issues

Sentiment score
7.0
Darwin's stability has improved, boasting 99% availability, though some issues persist; support is responsive, yet enhancements continue.
Sentiment score
7.2
Dremio users report stable performance overall, despite occasional memory leaks, scalability issues, and the need for frequent monitoring.
We refactored the query, and that worked, but it still doesn't make you confident to go to production with a product that might crash depending on the query you send it.
Data Architect at a consultancy with 51-200 employees
I rate Dremio a nine in terms of stability.
SR BI developer at BRQ Digital Solutions
 

Room For Improvement

Darwin users seek API integration, improved functionality, educational resources, and better automation for precision and transparency in AI processes.
Dremio users face issues with performance, connectors, learning curve, and desire better integration and schema flexibility.
Before we wrap up, I want to add that Dremio is lacking a semantic layer in a manner that the user can just choose dimensions, metrics, and filters to query the data.
Starburst comes with around 50 connectors now.
Senior Software Architect at USEReady
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.
SR BI developer at BRQ Digital Solutions
 

Setup Cost

Darwin's licensing costs are significant yet often seen as valuable, with predictable setup fees and optional costs for integrations.
Dremio offers cost-effectiveness but licensing is costly, leading some users to prefer the community version for scalability.
I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.
Data Engineer at a tech services company with 201-500 employees
Dremio does have a core of the engine that is open-source, but all the important features for the enterprise version are under license.
Data Architect at a consultancy with 51-200 employees
I had a good experience with pricing, as the pricing seems okay to me and the client.
 

Valuable Features

Darwin excels in data cleaning, model-building, and integration, enhancing productivity and accessibility for non-experts in machine learning.
Dremio excels in data virtualization, federated queries, and integration, enhancing data management and access with efficient tools.
Dremio has positively impacted my organization as nowadays we are connected to multiple databases from multiple environments, multiple APIs, and applications, and Dremio organizes everything in an amazing way for me.
Data Analyst at a insurance company with 501-1,000 employees
Reflections and automatic reflections speed up queries automatically based on usage, which means it detects what dimensions and measures are used the most and then materializes the answers upfront, speeding up the whole BI and analytics use case.
Having everything under one system and an easier-to-work-with interface, along with having API integrations, adds significant value to working with Dremio.
Data Consultant at a comms service provider with 201-500 employees
 

Categories and Ranking

Darwin
Ranking in Data Science Platforms
23rd
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
No ranking in other categories
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)
 

Mindshare comparison

As of November 2026, in the Data Science Platforms category, the mindshare of Darwin is 1.5%, up from 0.7% compared to the previous year. The mindshare of Dremio is 2.0%, down from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dremio2.0%
Darwin1.5%
Other96.5%
Data Science Platforms
 

Featured Reviews

AC
Founder at Helio Summit
Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.
There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.
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.
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Top Industries

By visitors reading reviews
Construction Company
15%
Manufacturing Company
12%
Financial Services Firm
12%
Outsourcing Company
11%
Financial Services Firm
22%
Outsourcing Company
8%
Comms Service Provider
8%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Large Enterprise2
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise6
Large Enterprise5
 

Questions from the Community

Ask a question
Earn 20 points
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...
 

Comparisons

 

Also Known As

No data available
Dremio AWS - BYOL
 

Overview

 

Sample Customers

Hunt Oil, Hitachi High-Tech Solutions
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Darwin vs. Dremio and other solutions. Updated: September 2026.
920,769 professionals have used our research since 2012.