Databricks vs Domino Data Science Platform comparison

Databricks and Domino Data Lab are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.4, while Domino Data Lab is ranked #17 with an average rating of 8.0. Databricks holds a 13.9% mindshare in Data Science Platforms, compared to Domino Data Lab’s 2.6% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Domino Data Lab users who would recommend it.

Databricks

Read 91 Databricks reviews

20,775 Views
8,933 Comparison Views

96% willing to recommend

Domino Data Science Platform

Read 2 Domino Data Science Platform reviews

1,360 Views
1,333 Comparison Views

100% willing to recommend

Databricks

Domino Data Science Platform

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Databricks and Domino Data Science Platform are competing products aimed at enhancing data science capabilities for enterprises. Databricks has an edge in scalability and integration with big data ecosystems, while Domino excels in data science management features.

Features: Databricks offers a Spark-based platform, strong data processing capabilities, and automated machine learning. Domino provides complete model management, collaboration tools, and support for various data science workflows. Domino's focus on model lifecycle management provides an advantage for end-to-end projects.

Ease of Deployment and Customer Service: Databricks offers cloud-native deployment and strong customer support, focusing on integration challenges. Domino allows flexible deployment, including on-premises options, and offers personalized customer service for smooth transitions. Organizational needs will dictate the choice between scalability and tailored setup.

Pricing and ROI: Databricks uses variable pricing based on usage, which can lead to cost efficiency and high ROI for large-scale implementations. Domino, although potentially higher in initial cost, offers substantial ROI through operational efficiency in collaborative projects. Financial decisions depend on budget and expected returns from each platform's offerings.

To learn more, read our detailed Databricks vs. Domino Data Science Platform Report (Updated: September 2025).

Buyer's Guide

Databricks vs. Domino Data Science Platform

September 2025

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Helped 868,706 peers since 2012

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

Databricks

Ranking in Data Science Platforms

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th), Streaming Analytics (1st)

Domino Data Science Platform

Ranking in Data Science Platforms

17th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Databricks is 13.9%, down from 19.2% compared to the previous year. The mindshare of Domino Data Science Platform is 2.6%, down from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	13.9%
Domino Data Science Platform	2.6%
Other	83.5%

Data Science Platforms

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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AHMEDSAHRAOUI

Machine Learning Engineer at Unemployed

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…

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Quotes from Members

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

Pros

"I haven't heard about any major stability issues. At this time I feel like it's stable."

"The solution is very easy to use."

"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."

"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."

"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."

"The solution offers a free community version."

"The integration with Python and the notebooks really helps."

"Databricks integrates well with other solutions."

More Databricks 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."

Cons

"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."

"Anyone who doesn't know SQL may find the product difficult to work with."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

"I would love an integration in my desktop IDE. For now, I have to code on their webpage."

"This solution only supports queries in SQL and Python, which is a bit limiting."

"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."

"I would like it if Databricks made it easier to set up a project."

"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."

More Databricks cons

"The deployment of large language models (LLMs) could be improved."

"The predictive analysis feature needs improvement."

Pricing and Cost Advice

"Databricks are not costly when compared with other solutions' prices."

"We only pay for the Azure compute behind the solution."

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"The pricing depends on the usage itself."

"I rate the price of Databricks as eight out of ten."

"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."

"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."

More Databricks pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

Manufacturing Company

Healthcare Company

Financial Services Firm

40%

Manufacturing Company

Insurance Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

No data available

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

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How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

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Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

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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.

See all answers

What is your primary use case for Domino Data Science Platform?

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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...

See all answers

Comparisons

Microsoft Power BI vs Databricks

Compared 9% of the time

Dataiku vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 5% of the time

More Databricks Competitors

Dataiku vs Domino Data Science Platform

Compared 25% of the time

Amazon SageMaker vs Domino Data Science Platform

Compared 19% of the time

Alteryx vs Domino Data Science Platform

Compared 8% of the time

KNIME Business Hub vs Domino Data Science Platform

Compared 8% of the time

Anaconda Business vs Domino Data Science Platform

Compared 6% of the time

More Domino Data Science Platform Competitors

Product Reports

Buyer's Guide

Databricks

September 2025

Download Databricks product report

Buyer's Guide

Data Science Platforms

September 2025

Download Domino Data Science Platform product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Domino Data Lab Platform

Interactive Demo

Demo not available

Databricks

Domino Data Lab

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Databricks

Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.

Domino Data Lab

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life

Buyer's Guide

Databricks vs. Domino Data Science Platform

September 2025

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