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Domino Data Science Platform vs Dremio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 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

Domino Data Science Platform
Ranking in Data Science Platforms
17th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Dremio
Ranking in Data Science Platforms
10th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
8
Ranking in other categories
Cloud Data Warehouse (6th)
 

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Domino Data Science Platform is 2.6%, down from 2.9% compared to the previous year. The mindshare of Dremio is 3.1%, down from 4.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Dremio3.1%
Domino Data Science Platform2.6%
Other94.3%
Data Science Platforms
 

Featured Reviews

AS
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…
KamleshPant - PeerSpot reviewer
Solution offers quick data connection with an edge in computation
It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS. It is a similar experience between the based application and cloud-based application. You just get the source, connect the data, get visualization, get connected, and do whatever you want. They say data reflection is one way where they do the caching and all that. Starburst also does the caching. In Starburst, you have a data product. Here, the data product comes from a reflection perspective. The y are working on a columnar memory map, columnar computation. That will have some edge in computation.

Quotes from Members

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

Pros

"The scalability of the solution is good; I'd rate it four out of five."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"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."
"Overall, you can rate it as eight out of ten."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"It's almost similar, yet it's better than Starburst in spinning up or connecting to the new source since it's on SaaS."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Dremio is very easy to use for building queries."
"Dremio allows querying the files I have on my block storage or object storage."
 

Cons

"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
"There are performance issues at times due to our limited experience with Dremio, and the fact that we are running it on single nodes using a community version."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"It shows errors sometimes."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"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."
"They need to have multiple connectors."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today."
 

Pricing and Cost Advice

Information not available
"Dremio is less costly competitively to Snowflake or any other tool."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
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Top Industries

By visitors reading reviews
Financial Services Firm
40%
Manufacturing Company
9%
Insurance Company
8%
Healthcare Company
5%
Financial Services Firm
29%
Computer Software Company
9%
Manufacturing Company
7%
Healthcare Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise3
Large Enterprise4
 

Questions from the Community

What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that cannot handle big deployments, which is not suitable for LLMs.
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying solely on data scientists might not be sufficient. I'd rate the solution eight out...
What do you like most about Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
The licensing is very expensive. We need a license to scale as we are currently using the community version.
What needs improvement with Dremio?
They need to have multiple connectors. Starburst is rich in connectors, however, they are lacking Salesforce connectivity as of today. They don't have Salesforce connectivity. However, Starburst do...
 

Also Known As

Domino Data Lab Platform
No data available
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Domino Data Science Platform vs. Dremio and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.