Category: Amazon Redshift

This post will explore brief history of zero-ETL, its importance for customers, and introduce an exciting new feature: history mode for Amazon Aurora PostgreSQL-Compatible Edition, Amazon Aurora MySQL-Compatible Edition, Amazon Relational Database Service (Amazon RDS) for MySQL, and Amazon DynamoDB zero-ETL integration with Amazon Redshift.

In this post, we explore the new higher base capacity of 1024 RPUs in Redshift Serverless, which doubles the previous maximum of 512 RPUs. This enhancement empowers you to get high performance for your workload containing highly complex queries and write-intensive workloads, with concurrent data ingestion and transformation tasks that require high throughput and low latency with Redshift Serverless.

At Open Universities Australia (OUA), we empower students to explore a vast array of degrees from renowned Australian universities, all delivered through online learning. In this post, we show you how we used AWS services to replace our existing third-party ETL tool, improving the team’s productivity and producing a significant reduction in our ETL operational costs.

In our previous thought leadership blog post Why a Cloud Operating Model we defined a COE Framework and showed why MuleSoft implemented it and the benefits they received from it. In this post, we’ll dive into the technical implementation describing how MuleSoft used Amazon EventBridge, Amazon Redshift, Amazon Redshift Spectrum, Amazon S3, & AWS Glue to implement it.

In this post, we show you how EUROGATE uses AWS services, including Amazon DataZone, to make data discoverable by data consumers across different business units so that they can innovate faster. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.

Amazon AppFlow bridges the gap between Google applications and Amazon Redshift, empowering organizations to unlock deeper insights and drive data-informed decisions. In this post, we show you how to establish the data ingestion pipeline between Google Analytics 4, Google Sheets, and an Amazon Redshift Serverless workgroup.

Amazon Redshift made significant strides in 2024, that enhanced price-performance, enabled data lakehouse architectures by blurring the boundaries between data lakes and data warehouses, simplified ingestion and accelerated near real-time analytics, and incorporated generative AI capabilities to build natural language-based applications and boost user productivity. This blog post provides a comprehensive overview of the major product innovations and enhancements made to Amazon Redshift in 2024.

DeNA Co., Ltd. (DeNA) engages in a variety of businesses, from games and live communities to sports & the community and healthcare & medical, under our mission to delight people beyond their wildest dreams. This post introduces a case study where DeNA combined Amazon Redshift Serverless and dbt (dbt Core) to accelerate data quality tests in their business.

In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. dbt on Athena supports real-time queries, while dbt on Amazon Redshift handles complex queries, unifying the development language and significantly reducing the technical learning curve. Using a single dbt modeling language not only simplifies the development process but also automatically generates consistent data lineage information. This approach offers robust adaptability, easily accommodating changes in data structures.

In this post, we continue from Accelerate Amazon Redshift secure data use with Satori – Part 1, and explain how Satori, an Amazon Redshift Ready partner, simplifies both the user experience of gaining access to data and the admin practice of granting and revoking access to data in Amazon Redshift. Satori enables both just-in-time and self-service access to data.