AWS Big Data Blog

Category: Amazon Redshift

Simplify data streaming ingestion for analytics using Amazon MSK and Amazon Redshift

Towards the end of 2022, AWS announced the general availability of real-time streaming ingestion to Amazon Redshift for Amazon Kinesis Data Streams and Amazon Managed Streaming for Apache Kafka (Amazon MSK), eliminating the need to stage streaming data in Amazon Simple Storage Service (Amazon S3) before ingesting it into Amazon Redshift. Streaming ingestion from Amazon […]

Simplify access management with Amazon Redshift and AWS Lake Formation for users in an External Identity Provider

Many organizations use identity providers (IdPs) to authenticate users, manage their attributes, and group memberships for secure, efficient, and centralized identity management. You might be modernizing your data architecture using Amazon Redshift to enable access to your data lake and data in your data warehouse, and are looking for a centralized and scalable way to […]

Enable Multi-AZ deployments for your Amazon Redshift data warehouse

November 2023: This post was reviewed and updated with the general availability of Multi-AZ deployments for provisioned RA3 clusters. Originally published on December 9th, 2022. Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical […]

Five actionable steps to GDPR compliance (Right to be forgotten) with Amazon Redshift

The GDPR (General Data Protection Regulation) right to be forgotten, also known as the right to erasure, gives individuals the right to request the deletion of their personally identifiable information (PII) data held by organizations. This means that individuals can ask companies to erase their personal data from their systems and any third parties with […]

Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). Apache Spark enables you to build applications in a variety […]

How AWS Payments migrated from Redash to Amazon Redshift Query Editor v2

AWS Payments is part of the AWS Commerce Platform (CP) organization that owns the customer experience of paying AWS invoices. It helps AWS customers manage their payment methods and payment preferences, and helps customers make self-service payments to AWS. The Machine Learning, Data and Analytics (MLDA) team at AWS Payments enables data-driven decision-making across payments […]

How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

This is a guest post co-written with Parag Doshi, Guru Havanur, and Simon Guindon from Tricentis. Tricentis is a global leader in continuous testing for DevOps, cloud, and enterprise applications. It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more […]

Simplify data ingestion from Amazon S3 to Amazon Redshift using auto-copy (preview)

Amazon Redshift is a fast, petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL and your existing business intelligence (BI) tools. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, delivering the best price-performance. […]

Run queries concurrently and see query history using Amazon Redshift Query Editor v2

Amazon Redshift is a fast, fully managed, petabyte-scale cloud data warehouse. You have the flexibility to choose from provisioned and serverless compute modes. You can start loading and querying large datasets conveniently in Amazon Redshift using Amazon Redshift Query Editor v2, a web-based SQL client application. Query Editor v2 empowers your technical and business teams […]

Automate data archival for Amazon Redshift time series tables

Amazon Redshift is a fast, petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse. You can […]