Tag: Amazon Redshift

One of the benefits of a data warehouse environment using both Amazon Redshift and Amazon RDS for PostgreSQL is that you can leverage the advantages of each service. Amazon Redshift is a high performance, petabyte-scale data warehouse service optimized for the online analytical processing (OLAP) queries typical of analytic reporting and business intelligence applications. On […]

When we first looked into the possibility of building a cloud-based data warehouse many years ago, we were struck by the fact that our customers were storing ever-increasing amounts of data, and yet only a small fraction of that data ever made it into a data warehouse or Hadoop system for analysis. We saw that […]

November 2022: This post was reviewed and updated for accuracy. Amazon Redshift Spectrum enables you to run Amazon Redshift SQL queries on data that is stored in Amazon Simple Storage Service (Amazon S3). With Amazon Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond the data that is stored natively in Amazon […]

In this post, we’ll demonstrate querying the Amazon Redshift audit data logged in S3 to provide answers to common use cases described preceding.

In April, we announced Amazon Redshift Spectrum in the AWS Blog. Redshift Spectrum is a new feature of Amazon Redshift that allows you to run complex SQL queries against exabytes of data in Amazon without having to load and transform any data. We’re happy to announce that Amazon QuickSight now supports Redshift Spectrum. Starting today, […]

In the healthcare field, data comes in all shapes and sizes. Despite efforts to standardize terminology, some concepts (e.g., blood glucose) are still often depicted in different ways. This post demonstrates how to convert an openly available dataset called MIMIC-III, which consists of de-identified medical data for about 40,000 patients, into an open source data […]

This blog post has been translated into Japanese and Chinese. Data warehousing workloads are known for high variability due to seasonality, potentially expensive exploratory queries, and the varying skill levels of SQL developers. To obtain high performance in the face of highly variable workloads, Amazon Redshift workload management (WLM) enables you to flexibly manage priorities and resource […]

Ian Meyers is a Solutions Architecture Senior Manager with AWS The serverless Amazon Redshift Monitoring utility lets you gather important performance metrics from your Redshift cluster’s system tables and persists the results in Amazon CloudWatch. This serverless solution leverages AWS Lambda to schedule custom SQL queries and process the results. With this utility, you can use […]

This blog post has been translated into Japanese.  Mixed workloads run batch and interactive workloads (short-running and long-running queries or reports) concurrently to support business needs or demand. Typically, managing and configuring mixed workloads requires a thorough understanding of access patterns, how the system resources are being used and performance requirements. It’s common for mixed […]

Organizations often grow organically—and so does their data in individual silos. Such systems are often powered by traditional RDBMS systems and they grow orthogonally in size and features. To gain intelligence across heterogeneous data sources, you have to join the data sets. However, this imposes new challenges, as joining data over dblinks or into a […]