Databricks on AWS
The simple, unified data platform seamlessly integrated with AWS
Databricks on AWS allows you to store and manage all your data on a simple, open lakehouse platform that combines the best of data warehouses and data lakes to unify all your analytics and AI workloads.
Why Databricks on AWS?
Simple
Databricks enables a single, unified data architecture on S3 for SQL analytics, data science and machine learning
12x 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
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. Read more.
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. Read more.
AWS Glue
Databricks’ integration with the 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. Read more.
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. Read more.
Enterprise Rollout
It’s important to carefully work through your rollout strategy — before you roll out Databricks across your enterprise. This page will help you understand the trade-offs so you can make the best decisions for your business. Read more.
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.
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Use Cases
