Review Summary
Users like Databricks Data Intelligence Platform for its user-friendly interface, efficient data processing capabili ...
Overview
Product Information on Databricks Data Intelligence Platform
Updated 13th October 2025
What is Databricks Data Intelligence Platform?
Databricks Data Intelligence Platform Pricing
Overall experience with Databricks Data Intelligence Platform
Engineer
10B - 30B USD, ManufacturingFAVORABLE
“A powerful and scalable data platform that unifies analytics and AI”
Overall, my experience has been very positive. It has helped us bring data engineering, analytics, and machine learning together in a single platform. Its performance, scalability, and flexibility have made it easier for teams to collaborate and deliver data-driven outcomes faster.
Director of Software Development
<50M USD, Healthcare and BiotechCRITICAL
“Limited Flexibility in Plotting and Dashboard Customization Noted by Users”
i like that its connected to my data and all under one platform
the biggest problem is the graphing is all little/no code so its super inflexible and things like venn diagram are not possible.
also the grid is delimited by 6 which means you cant evenly space out 4 components
also its annoying ai/bi dashboards and notebook dashboards are different
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Gartner Peer Insights recognizes vendors who meet or exceed both the market average Overall Experience and the market average User Interest and Adoption score through a Customers’ Choice distinction.
About Company
Company Description
Databricks is a global company focusing on data and AI. At the core of Databricks is the Databricks Data Intelligence Platform which allows entire organizations to use data and AI to power a wide range of business use cases. It's built on a lakehouse to provide an open, unified foundation for all data and governance and is powered by a Data Intelligence Engine that understands the uniqueness of the organizations’ data. Databricks simplifies and accelerates enterprises' data and AI goals by unifying data, analytics and AI on one platform. Its key mission is to assist data teams in addressing some of the world's most challenging problems.
Company Details
Company type
Private
Year Founded
2013
Head office location
San Francisco, United States
Number of employees
5001 - 10000
Website
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- Engineer10B+ USDManufacturingReview Source
A powerful and scalable data platform that unifies analytics and AI
Overall, my experience has been very positive. It has helped us bring data engineering, analytics, and machine learning together in a single platform. Its performance, scalability, and flexibility have made it easier for teams to collaborate and deliver data-driven outcomes faster. - Automation Engineer10B+ USDEnergy and UtilitiesReview Source
Databricks Excels at Scalability and Lakehouse Architecture but Faces Cost Concerns
it is outstanding because databricks came with innovation mindset into the market best of the class management , analysis and make the things operational . This is the core functions at which it excels. With the advent of Gen ai things will get better and better - Director of Software Development<50M USDHealthcare and BiotechReview Source
Limited Flexibility in Plotting and Dashboard Customization Noted by Users
i like that its connected to my data and all under one platform the biggest problem is the graphing is all little/no code so its super inflexible and things like venn diagram are not possible. also the grid is delimited by 6 which means you cant evenly space out 4 components also its annoying ai/bi dashboards and notebook dashboards are different - Engineer<50M USDMediaReview Source
Optimistic about unification of org use cases for data.
We love the idea of unifying many of our use cases across the org (analytics, interactive apps, dashboards, governance) under one powerful playform. - Data Analyst1B-10B USDServices (non-Government)Review Source
Automation Improves Data Quality While Overly Eager AI Suggestions Cause Frustration
It's been great! Allowing me to automate a lot of things I would usually have to do manually (or at least trigger manually) has massively contributed to our data quality.
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