Category: PostgreSQL compatible

Amazon Aurora combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open-source databases. Amazon Aurora is a global scale relational database service built for the cloud with drop-in MySQL and PostgreSQL compatibility. Amazon Aurora Global Database lets you span your Aurora database across multiple AWS Regions. This helps you recover from […]

When you migrate from Oracle to Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL, you may need to deal with partitioned tables and ensure global uniqueness across partitions. Oracle Database supports global indexes. A global index contains keys from multiple table partitions in a single index partition. Each table partition […]

In OLTP databases, the buffer cache is memory allocated for storing cached data and dirty pages. Cached data speeds up the retrieval of frequently accessed information, and reading from these cached pages minimizes disk I/O operations. Setting appropriate values for shared_buffers is important for optimal PostgreSQL performance and can lead to significant reductions in overall […]

In today’s data-driven world, JSON (JavaScript Object Notation) has emerged as a popular format for exchanging and storing data due to its simplicity and flexibility. As a result, database systems have evolved to include native support for JSON data types, enabling developers to work with JSON seamlessly within their applications. Oracle’s PL/JSON, an open-source package, […]

PostgreSQL is one of the most popular open-source relational database systems. The product of more than 30 years of development work, PostgreSQL has proven to be a highly reliable and robust database that can handle a large number of complicated data workloads. AWS offers services that make PostgreSQL database deployments straightforward to set up, manage, […]

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.