Fastest Cloud Data Warehouse
Amazon Redshift delivers up to 3x better price-performance than other cloud data warehouses. Amazon Redshift takes advantage of AWS designed-hardware and machine learning (ML) to deliver the best price performance at any scale. This includes using the AWS Nitro System to accelerate data compression and encryption, ML techniques to analyze queries, and graph optimization algorithms to automatically organize and store data for faster query results.
Introduction to Data Warehousing on AWS with Amazon Redshift (1:35)
Run high performance queries on petabytes of semi-structured and structured data so that you can build reports and dashboards using using Microsoft PowerBI, Tableau, QuickSight or other
business intelligence tools.
Real-Time Operational Insights
Bring together structured data from your data warehouse and semi-structured data from your S3 data lake to get real-time operational insights on your applications and systems.
Data as a Service
Share data inside and outside your organization for secure and governed collaboration on live data with Redshift data sharing.
Use SQL to automatically create, train, and deploy Amazon SageMaker machine learning (ML) models on the data in your data warehouse with Redshift ML.
Learn More About AWS Database Services
Database product offers from the AWS Free Tier.
Learn more about Amazon Redshift features
Browse through our collection of videos and tutorials to deepen your knowledge and experience with AWS
AQUA (Advanced Query Accelerator) for Amazon Redshift (1:54)
Amazon Redshift Concurrency Scaling (6:01)
Demo of Preview of Amazon Redshift ML (7:28)
Amazon Redshift RA3 Nodes: Overview and How to Upgrade (6:47)
Start with these free and simple tutorials to explore AWS database services
Deploy a Data Warehouse Using Amazon Redshift
In this project, you will create and configure an Amazon Redshift data warehouse, load sample data, and analyze it using a SQL client.
Migrate from Oracle to Amazon Redshift
In this tutorial, you will learn how to successfully migrate from Oracle to Amazon Redshift with minimal downtime.
Create and Connect to a MySQL Database using Amazon RDS
In this tutorial, you will learn how to create an environment to run your MySQL database (we call this environment an 'instance'), connect to the database, and delete the DB instance. We will do this using Amazon Relational Database Service (Amazon RDS) and everything done in this tutorial is free-tier eligible.
Create and Query a NoSQL Table using Amazon DynamoDB
In this tutorial, you will learn how to create a simple table, add data, scan and query the data, delete data, and delete the table by using the DynamoDB console. DynamoDB is a fully managed NoSQL database that supports both document and key-value store models. Its flexible data model, reliable performance, and auto scaling of throughput capacity make it a great fit for mobile, web, gaming, ad tech, IoT, and other applications. Everything in this tutorial is free-tier eligible.
Learn how Amazon Redshift has helped customers ingest, process, and report on their data to grow their businesses
Magellan Rx Management (Magellan Rx), a division of Magellan Health Inc., is a next-generation pharmacy organization that delivers meaningful solutions to the people it serves. Magellan Rx’s customers include health plans, employers, third-party administrators, union groups, and government agencies. To support its growing data needs and meet its service-level agreements, the organization needed to migrate from its on-premises data warehouse to a high-performing data hosting solution.
Nielsen is a global measurement and data analytics company, measuring what consumers watch and the advertising they’re exposed to. Nielsen migrated its National Television Audience Measurement platform to AWS. Then it built a new, cloud-native local television rating platform, "drastically increasing" the amount of data Nielsen ingests, processes, and reports to its clients each day.
Dollar Shave Club
Dollar Shave Club runs its entire ecommerce platform on AWS. As it grew, the company increasingly sought ways to gain more in-depth knowledge of customer trends and products so it could provide a more personalized customer experience. To support this vision, Dollar Shave Club began using two Amazon Redshift clusters as its primary data warehouse.
Nasdaq moved from a legacy on-premises data warehouse to an Amazon Web Services (AWS) data warehouse powered by an Amazon Redshift cluster. Between 2014 and 2018, this Amazon Redshift cluster grew to 70 nodes as the company expanded the solution to support all its North American markets. By 2018, the solution ingested financial market data from thousands of sources nightly, ranging from 30 billion to 55 billion records and surpassing 4 terabytes.