AWS Big Data Blog

Category: Amazon Redshift

Migrate a large data warehouse from Greenplum to Amazon Redshift using AWS SCT – Part 1

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 […]

Accelerate resizing of Amazon Redshift clusters with enhancements to classic resize

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 […]

Optimize your Amazon Redshift query performance with automated materialized views

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 […]

Achieve fine-grained data security with row-level access control in Amazon Redshift

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 […]

Accelerate machine learning with AWS Data Exchange and Amazon Redshift ML

July 2023: This post was reviewed for accuracy and updated. Amazon Redshift ML makes it easy for SQL users to create, train, and deploy ML models using familiar SQL commands. Redshift ML allows you to use your data in Amazon Redshift with Amazon SageMaker, a fully managed ML service, without requiring you to become an […]

Use AWS CloudWatch as a destination for Amazon Redshift Audit logs

Amazon Redshift is a fast, scalable, secure, and fully-managed cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL. Amazon Redshift has comprehensive security capabilities to satisfy the most demanding requirements. To help you to monitor the database for security and troubleshooting purposes, Amazon Redshift logs information […]

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Migrate from Snowflake to Amazon Redshift using AWS Glue Python shell

Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price-performance. Tens of thousands of customers use Amazon Redshift to analyze exabytes of data per day and power analytics workloads such as BI, predictive analytics, and real-time streaming analytics without having to manage the data warehouse infrastructure. It natively integrates with other AWS […]

Create cross-account, custom Amazon Managed Grafana dashboards for Amazon Redshift

Amazon Managed Grafana recently announced a new data source plugin for Amazon Redshift, enabling you to query, visualize, and alert on your Amazon Redshift data from Amazon Managed Grafana workspaces. With the new Amazon Redshift data source, you can now create dashboards and alerts in your Amazon Managed Grafana workspaces to analyze your structured and […]

Resize Amazon Redshift from DC2 to RA3 with minimal or no downtime

Amazon Redshift is a popular cloud data warehouse that allows you to process exabytes of data across your data warehouse, operational database, and data lake using standard SQL. Amazon Redshift offers different node types like DC2 (dense compute) and RA3, which you can use for your different workloads and use cases. For more information about […]

How GE Proficy Manufacturing Data Cloud replatformed to improve TCO, data SLA, and performance

This is post is co-authored by Jyothin Madari, Madhusudhan Muppagowni and Ayush Srivastava from GE. GE Proficy Manufacturing Data Cloud (MDC), part of the GE Digital’s Manufacturing Execution Systems (MES) suite of solutions, allows GED’s customers to increase the derived value easily and quickly from the MES by reliably bringing enterprise-wide manufacturing data into the […]