Category: PostgreSQL compatible

For workloads that require simpler orchestration of creating a staging environment for extensive testing and achieve maximum availability during a major version upgrade, we’re pleased to announce the general availability of Amazon RDS blue/green deployments for Amazon Aurora PostgreSQL-Compatible Edition and Amazon RDS for PostgreSQL for versions 11.21 and higher, 12.16 and higher, 13.12 and higher, 14.9 and higher, and 15.4 and higher in all applicable AWS Regions and AWS GovCloud (US) Regions. In this post, we walk through an example of creating a blue/green deployment. We also show how to perform major version upgrades using blue/green deployment with minimal downtime and describe the switchover process. Finally, we discuss the best practices for using blue/green deployment.

One of the migration patterns that you can use to modernize and migrate mainframe workloads is automated refactoring using Blue Age tooling. This pattern often requires you to unlock mainframe data from on-premises databases (like IBM Db2 for iSeries) in order to be able to move to the cloud and the technical constraints and steps […]

In this post, we provide an overview of database migration from IBM Db2 LUW to Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL. We discuss the challenges you may encounter during schema conversions, and how to perform data migration using the native EXPORT and COPY commands. Additionally, we address how […]

In this post, we guide you through the steps to setting up Amazon Aurora PostgreSQL-Compatible Edition database activity streams (DAS) for monitoring in IBM Guardium. Here, we are using IBM Guardium version 11.5. Aurora PostgreSQL-Compatible is a fully managed, PostgreSQL-compatible, ACID-compliant relational database engine that combines the speed, reliability, and manageability of Amazon Aurora with […]

Today’s modern applications are expected to be scalable and resilient. The top of this list is scalability, which depending on the size of the application workload could mean the ability to handle millions of users on demand. With stateful applications such as eCommerce, Financial Services and Games, this means having highly available databases. With the release of Amazon Aurora in 2015, customers could run relational databases in an Aurora cluster comprising of one writer and up to 15 low-latency reader nodes. This enables applications to scale reads significantly. However, as with any database supporting multiple instances, developers have built complex application logic to deal with special events such as switchover or failover.

In this post, we demonstrate how to create custom PostgreSQL data types using TLE. PostgreSQL ships with many robust data types that accommodate most customer workloads in a performant manner. Although PostgreSQL has the capabilities to deploy custom data types natively, introducing new data types at scale in architectures spanning multiple AWS accounts and Regions poses a unique challenge for builders. With Trusted Language Extensions (TLE), you can create and manage your custom data types, allowing the quick and easy deployment of PostgreSQL data types across your infrastructures in a secure and efficient manner.

April, 2026: Aurora Serverless v2 has been renamed Aurora serverless. No action required. Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL major versions are supported at least until the community end-of-life for the corresponding community versions. When the community PostgreSQL major version reaches its end of life, no further updates, security […]

It’s important to be aware of the case sensitivity of text data in PostgreSQL when performing queries or comparisons to ensure that the results match your intended expectations. Case also affects how the database performs sorting operations. By default, PostgreSQL is case sensitive when sorting or comparing string values. For example, PostgreSQL considers “amazon” and […]

In this post, we show you how to set up cross-account logical replication using Amazon Aurora PostgreSQL-Compatible Edition. By leveraging Aurora’s cross-account clone and PostgreSQL logical replication, you can achieve near real-time synchronization between a source and a target database in different AWS accounts. You can customize the solution to meet specific requirements, including selective […]

April, 2026: Aurora Serverless v2 has been renamed Aurora serverless. No action required. August, 2024: This post has been updated to reflect advances in technology and new features AWS released, to help you on your generative AI journey. Generative artificial intelligence (AI) has captured our imagination and is transforming industries with its ability to answer […]