Author: Thiyagarajan Arumugam

Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price-performance. It allows you to run complex analytic queries against terabytes to petabytes of structured and semi-structured data, using sophisticated query optimization, columnar on high-performance storage, and massively parallel query execution. At AWS, we embrace the culture that security is job zero, by […]

With a data lake built on Amazon Simple Storage Service (Amazon S3), you can use the purpose-built analytics services for a range of use cases, from analyzing petabyte-scale datasets to querying the metadata of a single object. AWS analytics services support open file formats such as Parquet, ORC, JSON, Avro, CSV, and more, so it’s […]

When migrating from a legacy data warehouse to Amazon Redshift, it is tempting to adopt a lift-and-shift approach, but this can result in performance and scale issues long term. This post guides you through the following best practices for ensuring optimal, consistent runtimes for your ETL processes.

Managing database users though federation allows you to manage authentication and authorization procedures centrally. Amazon Redshift now supports database authentication with IAM, enabling user authentication though enterprise federation. In this post, I demonstrate how you can extend the federation to enable single sign-on (SSO) to the Amazon Redshift data warehouse.