Redshift

Founded 2012

Run SQL analytics on petabytes of data in a cloud data warehouse

Cost

Free Tier

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Amazon Redshift to store and analyze large volumes of structured data using SQL. It connects to data lakes on Amazon S3, operational databases like Aurora and DynamoDB, and streaming services like Kinesis without requiring complex data pipelines. You can run BI reports, build ML models in SQL, query near real-time data, and use natural language to write queries via Amazon Q. It scales automatically with serverless options and integrates with tools like QuickSight, Tableau, and Power BI.

What Redshift does

Write SQL queries on petabytes of data across a data warehouse and data lakeSet up a serverless data warehouse that scales automatically with query loadSync transactional database changes into Redshift without managing ETL pipelinesBuild and train ML models using SQL inside the data warehouseConnect BI tools like Tableau or Power BI to Redshift for dashboard reportingQuery Amazon S3 data in Iceberg and Parquet formats without copying itUse Amazon Q to generate SQL from plain English descriptionsControl data access at row and column level for different user groupsServerless mode that auto-scales compute based on workload without any manual setupZero-ETL integrations that move data from Aurora, RDS, and DynamoDB into Redshift without pipelinesBuilt-in data lake query engine supporting Apache Iceberg and Parquet on Amazon S3Natural language SQL query generation using Amazon Q in the Redshift Query EditorGraviton-based RG instances running workloads up to 2.4x faster at 30% lower cost than RA3Row-level and column-level access controls included at no extra costUp to 7x faster query performance on first-run low-latency SQL queriesDirect integration with Amazon Bedrock for using Redshift data in generative AI applications