Name: Databricks AI/BI
Rating: 4.5 (31 reviews)

Overview

Product Information on Databricks AI/BI

Updated 30th March 2026

What is Databricks AI/BI?

Databricks AI/BI is a software that integrates artificial intelligence and business intelligence capabilities on a unified analytics platform. The software enables organizations to analyze and visualize structured or unstructured data, generate insights, and build and deploy machine learning models. Databricks AI/BI supports collaborative data workflows by allowing data engineers, analysts, and data scientists to work together within the platform. The software automates data preparation, feature engineering, and model selection processes, and provides tools for creating interactive dashboards and reports. Databricks AI/BI addresses the business problem of transforming raw data into actionable insights by streamlining analytics and machine learning tasks within a single environment.

Overall experience with Databricks AI/BI

Manager

1B - 3B USD, Banking

FAVORABLE

“Strong Data Processing Capabilities Not Ideal for Low Consumption AI Use Cases”

4.0

Mar 30, 2026

Very suited for data intensive workloads combined with AI, but to costly for lightweight operational AI use cases. Databricks seems a strong long term candidate in the new AI age, but it needs to be complemented with other technologies that are more cost-effective for light-weight use cases.

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CRITICAL

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

https://databricks.com

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User Sentiment About Databricks AI/BI

Reviewer Insights for: Databricks AI/BI

Databricks AI/BI Likes & Dislikes

Strong compute for data intensive workloads. It can process large volumes of data quickly for follow up tasks like insights or agentic decision making. The suite is also quite complete (not fully). With MLFlow a quick and easy development studio can be set up, while unity catalog allows fine grained enterprise wide data sharing.

What I personally like most about it is its unified architecture that seamlessly combines data engineering, analytics and AI in one platform and it also values how it simplifies workflows, enabling faster insights and more efficient decision making across organization.

1. The sheer time savings a tool like this offers is immense, 2. The democratisation of data is really helpful for less technical folk to get information at their fingertips, 3. Being able to describe outcomes in natural text rather than SQL is very useful.

The solution is quite costly, there are cheaper alternatives in the market that work just as well for certain use cases. If your use case has little data consumption, DBX is just to expensive. Also we are struggling with combining stateful agents with DBX, as it requires external state persistence. As such, if this is not available, an extra component needs to be introduced in the solution.

It can be difficult for beginners to get started due to its complexity. It can also become expensive if usage isn't carefully managed. Optimizing performance often requires experienced users.

1. Regional availability of Azure for Genie Agent is patchy, 2. The number of tables you can give to Genie is limited, 3. Cross-region data processing doesn't guarantee which region your data will be processed within.

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Market Guide for Agentic Analytics

1B-10B USD

Banking

Review Source

Strong Data Processing Capabilities Not Ideal for Low Consumption AI Use Cases

TECHNICAL CONSULTANT

50M-1B USD

IT Services

Databricks: A Scalable, Unified Lakehouse platform driving advanced analytics and AI with collaborative efficiency.

5.0

Apr 1, 2026

It is a powerful, unified platform for large scale data engineering, analytics and AI with excellent scalability and Lakehouse architecture. It also offers collaborative workspaces and seamless integration with major cloud providers.

SOFTWARE DEVELOPER

Services (non-Government)

It is a truly exceptional tool for enhancing internal decision making at breakneck speed.

Apr 4, 2026

With the time I have spent so far with Databricks Genie it has turned tasks that would ordinarily take hours into tasks that take seconds or minutes. However, as part of the rollout there have been some regional deployment issues that have prevented us from taking full advantage of the tool.

Engineering Manager

10B+ USD

Auto Generated Summaries Aid Reporting but Complex Queries Face Occasional Issues

Mar 31, 2026

The best part about working with this platform is our business users can interact with the datasets using NLP. They don't need to learn or hunt down someone with SQL expertise. The auto generated summaries in Lakeview are also great for executive facing reports. You drop in a chart and it writes takeaways in plain English. And all of these can be done through Unity catalog integration without maintaining a separate access layer. The thing we have struggled with is Genie. It can be hit or miss for complex questions where sometimes uses wrong window function logic. Also, the dashboards are limited in functionality compared to BI only tools. For example, you can't click on a bar in a chart and have it filter rest of the dashboard. It also sometimes has performance issues when dealing with large datasets.

DIRECTOR OF SOFTWARE DEVELOPMENT

<50M USD

Healthcare and Biotech

Frequent Container Updates Impact Database Script Stability and Git Repo Sync Difficulties

I use databricks to run several machine learning jobs on a schedule. One of the most important jobs, is the integration runtime agent which copies data from our production db to the data warehouse. The reliability has been very good, but at times it has been a struggle to keep pacakges updated with the various containers that are used. It seems every few months an update causes one of our db scripts to become flaky and we need to patch it.

Overview

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Overall experience with Databricks AI/BI

“Strong Data Processing Capabilities Not Ideal for Low Consumption AI Use Cases”