Category: Amazon Redshift

July 2023: This post was reviewed for accuracy. In the post Data preparation using Amazon Redshift with AWS Glue DataBrew, we saw how to create an AWS Glue DataBrew job using a JDBC connection for Amazon Redshift. In this post, we show you how to create a DataBrew profile job and a recipe job using […]

This is the sixth in a series of posts. We’re excited to share dozens of new features to automate your schema conversion; preserve your investment in existing scripts, reports, and applications; accelerate query performance; and potentially simplify your migrations from legacy data warehouses to Amazon Redshift. Check out all the previous posts in this series: […]

Building a robust data lake is very beneficial because it enables organizations have a holistic view of their business and empowers data-driven decisions. The curated layer of a data lake is able to hydrate multiple homogeneous data products, unlocking limitless capabilities to address current and future requirements. However, some concepts of how data lakes work […]

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Many customers look to build their data warehouse on Amazon Redshift, and they have many requirements where they want to convert data from row […]

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. As enterprise customers look to build their data […]

In this second post of a multi-part series, we share best practices for choosing the optimal Amazon Redshift cluster, data architecture, converting stored procedures, compatible functions and queries widely used for SQL conversions, and recommendations for optimizing the length of data types for table columns. You can check out the first post of this series […]

A data warehouse collects and consolidates data from various sources within your organization. It’s used as a centralized data repository for analytics and business intelligence. When working with on-premises legacy data warehouses, scaling the size of your data warehouse or improving performance can mean purchasing new hardware or adding more powerful hardware. This is often […]

October 2023: This post was reviewed and updated to include the latest enhancements in Amazon Redshift’s resize feature. Amazon Redshift has improved the performance of the classic resize feature for multi-node RA3 clusters and increased the flexibility of the cluster snapshot restore operation. You can use the classic resize operation to resize a cluster when […]

Amazon Redshift is a fast, fully managed cloud data warehouse database that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. Amazon Redshift allows you to analyze structured and semi-structured data and seamlessly query data lakes and operational databases, using AWS designed hardware and automated machine learning (ML)-based tuning to […]

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. One of the challenges with security is that enterprises want to provide fine-grained access control at the row level for sensitive data. You […]