AWS Big Data Blog
Category: Amazon Redshift
What to consider when migrating data warehouse to Amazon Redshift
Customers are migrating data warehouses to Amazon Redshift because it’s fast, scalable, and cost-effective. However, data warehouse migration projects can be complex and challenging. In this post, I help you understand the common drivers of data warehouse migration, migration strategies, and what tools and services are available to assist with your migration project. Let’s first […]
Federated access to Amazon Redshift clusters in AWS China Regions with Active Directory Federation Services
Many customers already manage user identities through identity providers (IdPs) for single sign-on access. With an IdP such as Active Directory Federation Services (AD FS), you can set up federated access to Amazon Redshift clusters as a mechanism to control permissions for the database objects by business groups. This provides a seamless user experience, and centralizes the governance […]
Accelerate your data warehouse migration to Amazon Redshift – Part 5
This is the fifth 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 the all the posts in this series: […]
Migrate your Amazon Redshift cluster to another AWS Region
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. Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS designed hardware and machine […]
Make data available for analysis in seconds with Upsolver low-code data pipelines, Amazon Redshift Streaming Ingestion, and Amazon Redshift Serverless
Amazon Redshift is the most widely used cloud data warehouse. Amazon Redshift makes it easy and cost-effective to perform analytics on vast amounts of data. Amazon Redshift launched Streaming Ingestion for Amazon Kinesis Data Streams, which enables you to load data into Amazon Redshift with low latency and without having to stage the data in […]
Build and deploy custom connectors for Amazon Redshift with Amazon Lookout for Metrics
Amazon Lookout for Metrics detects outliers in your time series data, determines their root causes, and enables you to quickly take action. Built from the same technology used by Amazon.com, Lookout for Metrics reflects 20 years of expertise in outlier detection and machine learning (ML). Read our GitHub repo to learn more about how to […]
Query and visualize Amazon Redshift operational metrics using the Amazon Redshift plugin for Grafana
Grafana is a rich interactive open-source tool by Grafana Labs for visualizing data across one or many data sources. It’s used in a variety of modern monitoring stacks, allowing you to have a common technical base and apply common monitoring practices across different systems. Amazon Managed Grafana is a fully managed, scalable, and secure Grafana-as-a-service […]
Automate Amazon Redshift load testing with the AWS Analytics Automation Toolkit
This blog post was last reviewed and updated July 2022, to be consistent with the new menu interface launched by the AWS Analytics Automation Toolkit. Amazon Redshift is a fast, fully managed, widely popular cloud data warehouse that powers the modern data architecture that empowers you with fast and deep insights and machine learning (ML) […]
Perform ETL operations using Amazon Redshift RSQL
Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tens of thousands of customers use Amazon Redshift to process exabytes of data per […]
ETL orchestration using the Amazon Redshift Data API and AWS Step Functions with AWS SDK integration
Extract, transform, and load (ETL) serverless orchestration architecture applications are becoming popular with many customers. These applications offers greater extensibility and simplicity, making it easier to maintain and simplify ETL pipelines. A primary benefit of this architecture is that we simplify an existing ETL pipeline with AWS Step Functions and directly call the Amazon Redshift […]