StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Utilities
  3. Analytics
  4. General Analytics
  5. Azure Databricks vs PowerBI

Azure Databricks vs PowerBI

OverviewComparisonAlternatives

Overview

PowerBI
PowerBI
Stacks385
Followers283
Votes0
Azure Databricks
Azure Databricks
Stacks252
Followers396
Votes0

Azure Databricks vs PowerBI: What are the differences?

Azure Databricks and PowerBI are two powerful tools used for data analytics and visualization. While they both serve the purpose of working with data, there are key differences that set them apart.
  1. Deployment and Integration: Azure Databricks is a cloud-based service that integrates with other Azure services, allowing for seamless deployment and integration with existing workflows. PowerBI, on the other hand, is a standalone business intelligence tool that can be deployed on-premises or in the cloud, but may require additional configurations to integrate with other systems.

  2. Data Processing and Analytics: Azure Databricks is built on the Apache Spark platform, providing scalable data processing capabilities for big data analytics. It offers advanced analytics features such as machine learning and streaming analytics. PowerBI, on the other hand, primarily focuses on data visualization and interactive reporting, with limited capabilities for data processing and analytics.

  3. Collaboration and Notebooks: Azure Databricks provides a collaborative environment for data scientists and analysts to work together on data and analytics projects. It offers the ability to create and share notebooks, which are interactive documents that contain code, visualizations, and documentation. PowerBI, on the other hand, allows collaboration through sharing and publishing reports and dashboards, but does not provide a notebook-like environment for code-based collaboration.

  4. Data Source Connectivity: Azure Databricks has extensive connectivity options, allowing users to connect to various data sources such as Azure storage, SQL databases, and data lakes. It supports both structured and unstructured data. PowerBI also offers a wide range of data connectors, but may require additional configurations or custom connectors for certain data sources.

  5. Scalability and Performance: Azure Databricks is designed to handle big data workloads and can scale horizontally by adding more compute resources. It leverages the distributed computing capabilities of Apache Spark to process large volumes of data efficiently. PowerBI, on the other hand, is more suited for smaller datasets and may experience performance limitations when dealing with large volumes of data.

  6. Customization and Embedded Analytics: PowerBI offers a high level of customization, allowing users to create custom visuals and embed them into other applications or websites. It also provides APIs and SDKs for developers to build custom solutions. Azure Databricks, on the other hand, focuses more on data processing and analytics, with limited customization options and no built-in support for embedding analytics into other applications.

In summary, Azure Databricks is a cloud-based data processing and analytics platform with extensive integration capabilities and collaboration features, while PowerBI is a standalone business intelligence tool focused on data visualization and reporting with customization and embedding options.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

PowerBI
PowerBI
Azure Databricks
Azure Databricks

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.

-
Optimized Apache Spark environment; Autoscale and auto terminate; Collaborative workspace; Optimized for deep learning; Integration with Azure services; Support for multiple languages and libraries
Statistics
Stacks
385
Stacks
252
Followers
283
Followers
396
Votes
0
Votes
0
Pros & Cons
Cons
  • 1
    Need to use work or school account to use
No community feedback yet
Integrations
No integrations available
Scala
Scala
Azure DevOps
Azure DevOps
Databricks
Databricks
Python
Python
GitHub
GitHub
Apache Spark
Apache Spark
.NET for Apache Spark
.NET for Apache Spark

What are some alternatives to PowerBI, Azure Databricks?

Google Analytics

Google Analytics

Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications.

Mixpanel

Mixpanel

Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience.

Piwik

Piwik

Matomo (formerly Piwik) is a full-featured PHP MySQL software program that you download and install on your own webserver. At the end of the five-minute installation process, you will be given a JavaScript code.

Clicky

Clicky

Clicky Web Analytics gives bloggers and smaller web sites a more personal understanding of their visitors. Clicky has various features that helps stand it apart from the competition specifically Spy and RSS feeds that allow web site owners to get live information about their visitors.

Plausible

Plausible

It is a lightweight and open-source website analytics tool. It doesn’t use cookies and is fully compliant with GDPR, CCPA and PECR.

Databricks

Databricks

Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.

userTrack

userTrack

userTrack is now called UXWizz. Get access to better insights, a faster dashboard and increase user privacy. It provides detailed visitor insights without relying on third-parties.

Quickmetrics

Quickmetrics

It is a service for collecting, analyzing and visualizing custom metrics. It can be used to track anything from signups to server response times. Sending events is super simple.

Matomo

Matomo

It is a web analytics platform designed to give you the conclusive insights with our complete range of features. You can also evaluate the full user-experience of your visitor’s behaviour with its Conversion Optimization features, including Heatmaps, Sessions Recordings, Funnels, Goals, Form Analytics and A/B Testing.

Maze

Maze

Maze empowers product and marketing teams to test anything from prototypes to copy, or round up user feedback—all in one place. Rapidly collect user insights across teams and create better user experiences, together.

Related Comparisons

Postman
Swagger UI

Postman vs Swagger UI

Mapbox
Google Maps

Google Maps vs Mapbox

Mapbox
Leaflet

Leaflet vs Mapbox vs OpenLayers

Twilio SendGrid
Mailgun

Mailgun vs Mandrill vs SendGrid

Runscope
Postman

Paw vs Postman vs Runscope