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 8.3, while Domino Data Lab is ranked #18 with an average rating of 8.0. Databricks holds a 9.3% mindshare in Data Science Platforms, compared to Domino Data Lab’s 2.2% 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 93 Databricks reviews

18,865 Views
8,112 Comparison Views

96% willing to recommend

Domino Data Science Platform

Read 2 Domino Data Science Platform reviews

1,358 Views
1,331 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: December 2025).

Buyer's Guide

Databricks vs. Domino Data Science Platform

December 2025

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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), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)

Domino Data Science Platform

Ranking in Data Science Platforms

18th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of Databricks is 9.3%, down from 18.8% compared to the previous year. The mindshare of Domino Data Science Platform is 2.2%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	9.3%
Domino Data Science Platform	2.2%
Other	88.5%

Data Science Platforms

Featured Reviews

Satyam Wagh

Consultant at Nice Software Solutions

Unified data workflows have cut ticket processing times and are driving faster business insights

Databricks already provides monthly updates and continuously works on delivering new features while enhancing existing ones. However, the platform could become easier to use. While instruction-led workshops are available, offering more free instructional workshops would allow a wider audience to access and learn about Databricks. Additionally, providing use cases would help beginners gain more knowledge and hands-on experience. Regarding my experience, I was initially unfamiliar with the platform and had to conduct research and learn through various videos. I did find some instruction-led classes, but several of those required payment. The platform should provide more free resources to enable a broader audience to access and learn about Databricks. The platform itself is user-friendly and easy to use without complex issues, so I believe it does not need improvement in its core functionality. Rather, supporting aspects can be enhanced.

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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

"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."

"The initial setup phase of Databricks was good."

"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."

"I think Databricks is very good at facilitating AI and machine learning projects; they implement AI and machine learning models very well, and clients can run their models on Databricks."

"Databricks is a scalable solution. It is the largest advantage of the solution."

"The ability to stream data and the windowing feature are valuable."

"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"

"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."

More Databricks pros

"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."

"The scalability of the solution is good; I'd rate it four out of five."

Cons

"The product should provide more advanced features in future releases."

"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."

"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."

"The pricing of Databricks could be cheaper."

"Performance could be improved."

"I have seen better user interfaces, so that is something that can be improved."

"We'd like a more visual dashboard for analysis It needs better UI."

"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."

More Databricks cons

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

"The predictive analysis feature needs improvement."

Pricing and Cost Advice

"The cost is around $600,000 for 50 users."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

"I would rate the tool’s pricing an eight out of ten."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"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."

"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."

"We're charged on what the data throughput is and also what the compute time is."

"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."

More Databricks pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

Healthcare Company

Financial Services Firm

39%

Manufacturing Company

Insurance Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	26
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

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Compared 22% of the time

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Compared 11% of the time

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Compared 9% of the time

Alteryx vs Domino Data Science Platform

Compared 6% of the time

Microsoft Azure Machine Learning Studio vs Domino Data Science Platform

Compared 4% of the time

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Product Reports

Buyer's Guide

Databricks

February 2026

Download Databricks product report

Buyer's Guide

Data Science Platforms

February 2026

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 offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.

Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.

What features make Databricks unique?

Notebook: Enables collaborative work among team members.
Delta Lake: Optimizes data management operations.
Unity Catalog: Provides governance over data assets.
Cloud Integration: Seamlessly connects with major cloud platforms.

What benefits can users expect from Databricks?

Versatility: Supports diverse applications in data science and engineering.
Performance: Delivers efficient handling of large-scale analytics tasks.
Collaboration: Enhances teamwork in data projects.
Unified Environment: Centralizes machine learning and analytics activities.

In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.

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

December 2025

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