Databricks on AWS

The simple, unified data platform seamlessly integrated with AWS services

Databricks on AWS allows you to store and manage all of your data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes to unify all of your analytics and AI workloads.

Reliable data engineering

SQL Analytics on all your data

Collaborative data science

Production machine learning

Why Databricks on AWS?

Simple

Databricks enables a single, unified data architecture on S3 for SQL analytics, data science and machine learning

4x better price-performance

Get data warehouse performance at data lake economics through SQL-optimized compute clusters

Proven

Thousands of customers have implemented Databricks on AWS to provide a game-changing analytics platform that addresses all analytics and AI use cases

Trusted by customers in every industry

Dollar Shave Club: Personalizing customer experiences with Databricks

Download eBook

Hotels.com: Optimizing the customer experience with machine learning

Download case study

HP: From data prep to deep learning — how HP unifies analytics with Databricks

Watch on-demand webinar

Finra

Human Longevity Inc

NBC Universal

JP Morgan

Animo

Viacom

Riot Game

edmunds

Sanford Health

Bethesda

McGrawHill

Nasdaq

Regeneron

Zynga

Conde Nast

Featured integrations

AWS Security

Databricks integrates with Amazon security and single sign-on, making it easy to roll out across your organization. Users can access Databricks using AWS SSO without the need for managing a separate set of credentials.

Amazon Redshift

Databricks built-in integration with Redshift supports fast and easy transfer of data. Use Databricks to prepare data for Redshift with fast and reliable data pipelines, and access data from Redshift for advanced analytics.

AWS Glue

Databricks integration with AWS Glue service allows you to easily share Databricks table metadata from a centralized catalog across multiple Databricks workspaces, AWS services, applications, or AWS accounts. This enables users to easily access tables in Databricks from other AWS services, such as Athena.

Amazon SageMaker

Databricks is integrated with Amazon SageMaker using MLflow to enable the deployment of machine learning models for real-time model serving and REST API integration.

Enterprise Roll-Out

It’s important to carefully work through your roll-out strategy — before you roll out Databricks across your enterprise. This page will help you understand the tradeoffs so you can make the best decisions for your business

Free Databricks
Training on AWS

Databricks makes your S3 data lake analytics ready, and provides streamlined workflows and an interactive workspace that enables collaboration among data scientists, data engineers and business analysts. In this free three-part training series, we’ll teach you how to get started building a data lakehouse with Databricks, so you can begin to understand its capabilities and how data analysts can leverage SQL to query data in the lakehouse. You will learn how to train a machine learning (ML) model using customer product usage data with Databricks.

Use cases

Personalized recommendation engines

Process all of your data in real time to provide the most relevant product and service recommendations.

Genomic sequencing

Modernize your technology stack to improve experience for patients and physicians with the fastest DNASeq pipeline at scale.

Fraud detection and prevention

Leverage complete historical data together with real-time data streams to quickly identify anomalous and suspicious financial transactions.