Amazon Redshift

Power data driven decisions with the best price-performance cloud data warehouse

Why Amazon Redshift?

Tens of thousands of customers use Amazon Redshift every day to modernize their data analytics workloads and deliver insights for their businesses. With a fully managed, AI powered, massively parallel processing (MPP) architecture, Amazon Redshift drives business decision making  quickly and cost effectively. AWS’s zero-ETL approach unifies all your data for powerful analytics, near real-time use cases and AI/ML applications. Share and collaborate on data easily and securely within and across organizations, AWS regions and even 3rd party data providers, supported with leading security capabilities and fine-grained governance. 


Achieve up to 6x better price performance than any other cloud data warehouse, with a fully managed, AI powered, Massively Parallel Processing (MPP) data warehouse built for performance, scale, and availability.
Easily access or ingest data across your data lakes, databases, data warehouses, streaming data - with no code/low code zero-ETL approach for integrated analytics
Run SQL queries and open source analytics, power dashboards and visualizations, activate near real-time analytics and AI/ML applications with analytics engines and languages of your choice.
Share and collaborate on data easily within and across your organizations, AWS regions, and even 3rd party data sets with no manual data movement or copying and with fine grained governance, security, and compliance.

How it works

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning to deliver the best price performance at any scale.

Use cases

Ingests hundreds of megabytes of data per second so you can query data in near real time and build low latency analytics applications for fraud detection, live leaderboards, and IoT.

Build insight-driven reports and dashboards using Amazon Redshift and BI tools such as Amazon QuickSight, Tableau, Microsoft PowerBI, or others.

Use SQL to build, train, and deploy ML models for many use cases including predictive analytics, classification, regression and more to support  advance analytics on large amount of data.

Build applications on top of all your data across databases, data warehouses, and data lakes. Seamlessly and securely share and collaborate on to create more value for your customers, monetize your data as a service, and unlock new revenue streams.

Whether it's market data, social media analytics, weather data or more, subscribe to and combine third party data in AWS Data Exchange with your data in Amazon Redshift, without hassling over licensing and onboarding processes and moving the data to the warehouse.

Amazon Redshift Serverless

Easily run and scale analytics in seconds without provisioning and managing a data warehouse

Try Amazon Redshift Serverless »

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