Category: HAQM Redshift

Today, we are making our Dense Compute (DC) family faster and more cost-effective with new second-generation Dense Compute (DC2) nodes at the same price as our previous generation DC1. DC2 is designed for demanding data warehousing workloads that require low latency and high throughput. DC2 features powerful Intel E5-2686 v4 (Broadwell) CPUs, fast DDR4 memory, and NVMe-based solid state disks.

Deriving insights from large datasets is central to nearly every industry, and life sciences is no exception. To combat the rising cost of bringing drugs to market, pharmaceutical companies are looking for ways to optimize their drug development processes. They are turning to big data analytics to better quantify the effect that their drug compounds […]

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. HAQM Redshift Spectrum enables you to run HAQM Redshift SQL queries on data that is stored in HAQM Simple Storage Service (HAQM S3). With HAQM Redshift Spectrum, you can extend the analytic power of HAQM Redshift beyond the data that is stored natively in HAQM […]

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

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, HAQM Redshift workload management (WLM) enables you to flexibly manage priorities and resource […]

Ian Meyers is a Solutions Architecture Senior Manager with AWS The serverless HAQM Redshift Monitoring utility lets you gather important performance metrics from your Redshift cluster’s system tables and persists the results in HAQM 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 […]