Databricks logo - Data Analytics brand identity

Databricks (2026)

Expert Reviewed
by Dr. William BobosLast reviewed: Jan 2, 2026

Bring AI to your data. Bring AI to the world.

Visit Tool
Admin Verified
4 reviews
4.0
Monthly users
4.3M
Pricing
Pay-per-Use · Enterprise
Platform
Web App · CLI Tool

Overview

Databricks is the Data and AI company offering a Data Intelligence Platform with open lakehouse architecture. Founded in 2013 by creators of Apache Spark, Delta Lake, MLflow, and Unity Catalog, it unifies data, governance, and AI. The platform enables all users—from technical teams to business analysts—to discover, analyze, and operationalize data via aut...

Databricks Data Analytics showing Data Analytics - Bring AI to your data. Bring AI to the world.

Tool Details

Pricing Details
Pay-per-use based on DBUs. Premium tier: Jobs Compute $0.30/DBU-hour, All-Purpose Compute $0.55/DBU-hour, SQL Compute $0.22/DBU-hour, SQL Pro Compute $0.55/DBU-hour, Serverless SQL $0.70/DBU-hour. Additional cloud costs apply. Enterprise pricing higher (15-25% more). Free 14-day trial available.

Monthly Active Users
4.3M
Global Rank
#7,255

Figures above in this panel are rounded for quick orientation. Sign in for exact visits, rank breakdown, and engagement metrics.

Country Rank
Category Rank
Bounce Rate
Pages per Visit
Average Visit Duration

GDPR Compliant
No
NSFW
No
Demo Available
Yes
Accessibility
Requires Authentication

Input Formats
Databricks supports various data formats including CSV, Parquet, JSON, and more. Users can easily import and work with different types of data.
Output Formats
Users can export results and visualizations from Databricks in multiple formats such as CSV, Parquet, JSON, and more for further analysis or sharing.
SDKs
Python
JVM (Java/Kotlin/Scala)
.NET (C#)
R/MATLAB
Other
Hosting
Global
Integrations
Plugin/Integration
Supported Languages
Python, Scala, R, SQL

Company
Databricks
Country
Open Source
No
Last Updated
January 2, 2026

Key Features

Visual analytics

Share visualizations with stakeholders via links, embeds, or scheduled email reports. Databricks plugs into Plugin/Integ

Device-agnostic access

Multi-platform support ensures everyone can use Databricks regardless of their device preference. Databricks serves two

Developer-friendly API

Rate limits and authentication are clearly documented for smooth implementation.

Client libraries available

5 SDKs (e.g., Python, JVM (Java/Kotlin/Scala), and .NET (C#)) help dev teams launch prototypes quickly.

Try before you commit

Live demos and sandboxes simplify evaluation across stakeholders.

Support & service excellence

Databricks unifies tickets, context, and communication so agents resolve faster. Databricks can help customer-facing tea

Expert Insight

Dr. William Bobos

Databricks earns a 4.0/5 rating from 3 user reviews, with Dr. William Bobos recommending it for Data Analytics use cases. Dr. William Bobos's background in AI tools makes this recommendation especially relevant for software developers seeking AI tools tools.

Video Showcase

AI Agents with Databricks in 5 Minutes

Rate this Tool

4.0 / 5based on 4 ratings

User Reviews

4.0

Based on user reviews

Rating Distribution

5
0 (0%)
4
3 (100%)
3
0 (0%)
2
0 (0%)
1
0 (0%)

All Reviews

No reviews yet. Be the first to share your experience!

About Databricks

Bring AI to your data. Bring AI to the world.

Databricks is a data analytics tool developed by Databricks (US) designed for software developers, scientists and business executives. Databricks is a Data Intelligence Platform solution for software developers, data scientists, and business executives that unifies data engineering, analytics, and AI on an open lakehouse architecture founded by Apache Spark creators. Pricing: Pay-per-Use, Enterprise. With over 4.3 million monthly visits, Databricks has established a significant user base. The tool operates on a pay-per-use / enterprise pricing model. It is available on Web App, CLI Tool and API. Developer integration is supported through Python, JVM (Java/Kotlin/Scala), .NET (C#), R/MATLAB and Other SDKs. Databricks integrates with Plugin/Integration. It competes in the same space as Snowflake, Google BigQuery and Amazon Redshift. Explore more data analytics tools or browse all categories.

Databricks Snapshot

Key facts we track so you can judge fit before visiting the provider.

Primary category
Data Analytics
Best fit
Software Developers, Scientists, Business Executives
Platforms
Web App, CLI Tool, API
Provider context
Databricks - US
Known integrations
Plugin/Integration
Developer access
API documentation, Python, JVM (Java/Kotlin/Scala), .NET (C#) +2 more
Data handling
Global hosting, Privacy policy linked

Before you choose Databricks

  • Confirm Databricks's current limits, renewal terms, and seat pricing on the official site.
  • Review privacy, retention, and data-processing terms before using sensitive data.
  • Test the integrations or API path against one real workflow before rollout.
  • Make sure the supported platform matches where your team actually works.

Listing data is compiled from structured provider information, public signals, submissions, and periodic checks where available. Treat this page as a shortlist aid, then verify pricing, compliance, and product limits with the provider before making a business-critical decision.

How Databricks Works

Understanding the core functionality and approach of Databricks.

Databricks automates the path from data ingestion to insight delivery. Teams spend less time wrangling spreadsheets and more time acting on findings. Scheduled reports and alerts keep stakeholders informed without manual effort.

Key Features

Explore what makes Databricks stand out.

Visual analytics

Share visualizations with stakeholders via links, embeds, or scheduled email reports. Databricks plugs into Plugin/Integration so data stays in sync.

Device-agnostic access

Multi-platform support ensures everyone can use Databricks regardless of their device preference. Databricks serves two audiences: Web App, CLI Tool, and API apps for daily use, plus Python, JVM (Java/Kotlin/Scala), and .NET (C#) SDKs for custom builds.

Developer-friendly API

Rate limits and authentication are clearly documented for smooth implementation.

Client libraries available

5 SDKs (e.g., Python, JVM (Java/Kotlin/Scala), and .NET (C#)) help dev teams launch prototypes quickly.

Try before you commit

Live demos and sandboxes simplify evaluation across stakeholders.

Support & service excellence

Databricks unifies tickets, context, and communication so agents resolve faster. Databricks can help customer-facing teams if its AI outputs stay grounded in approved support material.

Use Cases

Discover how different audiences leverage Databricks.

Scientists

Distributed team workflows

Cross-platform sync ensures work started on one device continues seamlessly on another.

Software Developers

Accelerate development

With SDKs and webhooks, engineers connect Databricks to deployments, CI/CD, and monitoring pipelines.

FAQ about Databricks

What is Databricks and what does it do?

Databricks is Bring AI to your data. Bring AI to the world.. Databricks is the Data and AI company offering a Data Intelligence Platform with open lakehouse architecture. Founded in 2013 by creators of Apache Spark, Delta Lake, MLflow, and Unity Catalog, it unifies data, governance, and AI. The platform enables all users—from technical teams to business analysts—to discover, analyze, and operationalize data via automation and natural language processing. Key capabilities include Agent Bricks for AI agents, Lakebase for operational databases, and Databricks One for business users. Trusted by over 15,000-20,000 organizations worldwide, including 60%+ of the Fortune 500, with annualized revenue run rate exceeding $4.8B. Available on Web App, CLI Tool, API, Databricks is designed to enhance productivity and deliver professional-grade data analytics capabilities.

How much does Databricks cost?

Databricks offers Pay-per-Use, Enterprise pricing options. Pay-per-use based on DBUs. Premium tier: Jobs Compute $0.30/DBU-hour, All-Purpose Compute $0.55/DBU-hour, SQL Compute $0.22/DBU-hour, SQL Pro Compute $0.55/DBU-hour, Serverless SQL $0.70/DBU-hour. Pricing is designed to scale with your needs, from individual users to enterprise teams. For the most current pricing details and plan comparisons, visit the official Databricks pricing page or contact their sales team for custom enterprise quotes. Browse AI tools by pricing model to compare options.

Is Databricks secure and compliant with data privacy regulations?

Databricks takes data privacy seriously and implements industry-standard security measures. Data is hosted in Global, providing transparency about where your information resides. For comprehensive details about data handling, encryption, and privacy practices, review their official privacy policy. Security and compliance are continuously updated to meet evolving industry standards.
What platforms does Databricks support?
Databricks is available on Web App, CLI Tool, API. The web application provides full functionality directly in your browser without requiring downloads. API access allows developers to integrate Databricks capabilities directly into their own applications and workflows. This multi-platform approach ensures you can use Databricks wherever and however you work best.
How can I try Databricks before purchasing?
Databricks offers a demo version that lets you explore key features hands-on. Databricks typically offers trial periods or limited access to help you evaluate the platform. Testing the platform before committing ensures it meets your specific requirements and integrates smoothly with your existing workflows. Support for Python, Scala, R, SQL makes it accessible to global users.
What file formats does Databricks support?
Databricks accepts Databricks supports various data formats including CSV, Parquet, JSON, and more. Users can easily import and work with different types of data. as input formats, making it compatible with your existing files and workflows. Output is delivered in Users can export results and visualizations from Databricks in multiple formats such as CSV, Parquet, JSON, and more for further analysis or sharing., ensuring compatibility with downstream tools and platforms. This format flexibility allows seamless integration into diverse tech stacks and creative pipelines.
Who develops and maintains Databricks?
Databricks is developed and maintained by Databricks, based in US. Most recently updated in January 2026, the platform remains actively maintained with regular feature releases and bug fixes. This ongoing commitment ensures Databricks stays competitive and aligned with industry best practices.
How do I get access to Databricks?
Databricks is requires user registration and authentication for access. Create an account through the official website to begin your onboarding process. A demo version is also available for those who want to explore features before committing.
How is usage measured and billed in Databricks?
Databricks uses Credits, Pay-as-You-Go, Storage as billing metrics. Credit-based systems offer flexibility, allowing you to purchase credits in advance and consume them as needed. This usage model ensures you only pay for what you actually use, avoiding unnecessary overhead costs for features you don't need.
What deployment options does Databricks offer?
Databricks supports Cloud deployment configurations. Cloud-hosted options provide instant scalability without infrastructure management overhead. Choose the deployment model that best aligns with your technical requirements, security constraints, and operational preferences.

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Keep Databricks's listing accurate

Providers can update product facts, pricing context, screenshots, and launch notes. Paid placements are labeled separately and do not replace editorial or data-quality review.

How to Evaluate Databricks

Compare Databricks with Snowflake, Google BigQuery, Amazon Redshift and other alternatives before you decide. The goal is not to pick the most popular product; it is to find the tool that fits your actual workflow, risk level, and budget.

  1. Step 1Run the demo with one real software developers task, not a sample prompt.
  2. Step 2Model the full monthly cost at your expected usage, including seats, limits, and overages.
  3. Step 3Verify the integration path with your existing stack before you commit.
  4. Step 4Review privacy, retention, and compliance terms before using sensitive data.

Use the video walkthrough to check whether the interface matches the claims. For developer teams, inspect the Python SDK and JVM (Java/Kotlin/Scala), .NET (C#), R/MATLAB, Other support. Review the API documentation for auth, rate limits, errors, and export behavior. For broader context, browse more data analytics tools for software developers, or compare this page against the category hub. New to AI tool evaluation? Start with AI Tool Navigator.

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