Category: PostgreSQL compatible

Amazon Aurora PostgreSQL-Compatible Edition supports managed blue/green deployments to help reduce downtime and minimize risk during updates. Even with thorough planning and testing in non-production environments, unexpected issues can emerge after a version upgrade. In these cases, having a rollback plan is essential to quickly restore service stability. While the managed Blue/Green deployment feature doesn’t currently include built-in rollback functionality, you can implement alternative solutions for version management. In this post, we show how you can manually set up a rollback cluster using self-managed logical replication to maintain synchronization with the newer version after an Amazon RDS Blue/Green deployment switchover.

In this post, we explore how a leading AWS customer in the learning services industry successfully modernized its legacy SAP ASE environment by migrating to Amazon Aurora PostgreSQL-Compatible Edition. Partnering with AWS, the customer engineered a comprehensive migration strategy to transition from a proprietary system to an open source database while providing high availability, performance optimization, and cost-efficiency.

In this post, we introduce the AWS Database Acceleration Toolkit (DAT), an open source database accelerator. DAT is an infrastructure as code solution using Terraform to simplify and automate initial setup, provisioning, and on-going maintenance activities for Amazon Aurora.

Data validation is an important process during data migrations, helping to verify that the migrated data matches the source data. In this post, we present alternatives you can use for data validation when dealing with tables that lack primary keys. We discuss alternative approaches, best practices, and potential solutions to make sure that your data migration process remains thorough and reliable, even in the absence of traditional primary key-based validation methods. Specifically, we demonstrate how to perform data validation after a full load migration from SQL Server to Amazon Aurora PostgreSQL-Compatible Edition using the PostgreSQL tds_fdw extension.

In this post, we provide the steps to migrate a PostgreSQL database from Google Cloud SQL to RDS for PostgreSQL and Aurora PostgreSQL using the pglogical extension. We also demonstrate the necessary connection attributes required to support the database migration. The pglogical extension works for the community PostgreSQL version 9.4 and higher, and is supported on RDS for PostgreSQL and Aurora PostgreSQL as of version 12+.

Organizations are increasingly seeking to modernize their database infrastructure by migrating from legacy database engines such as Microsoft SQL Server and Oracle to more cost-effective and scalable open source alternatives such as PostgreSQL. This transition not only reduces licensing costs but also unlocks the flexibility and innovation offered by PostgreSQL’s rich feature set. In this post, we demonstrate how to convert and test database code from Microsoft SQL Server and Oracle to PostgreSQL using the generative AI capabilities of Amazon Bedrock.

In this post, we explore how pgvector 0.8.0 on Aurora PostgreSQL-Compatible delivers up to 9x faster query processing and 100x more relevant search results, addressing key scaling challenges that enterprise AI applications face when implementing vector search at scale.

In this post, we describe a solution to integrate generative AI applications with relational databases like Amazon Aurora PostgreSQL-Compatible Edition using RDS Data API (Data API) for simplified database interactions, Amazon Bedrock for AI model access, Amazon Bedrock Agents for task automation and Amazon Bedrock Knowledge Bases for context information retrieval.

In this post, we demonstrate how upgrading to Graviton4-based R8g instances with Aurora PostgreSQL-Compatible 17.4 on Aurora I/O-Optimized cluster configuration can deliver significant price-performance gains – delivering up to 1.7 times higher write throughput, 1.38 times better price-performance and reducing commit latency by up to 46% on r8g.16xlarge instances and 38% on r8g.2xlarge instances as compared to Graviton2-based R6g instances.

pgTAP (PostgreSQL Test Anything Protocol) is a unit testing framework that empowers developers to write and run tests directly within the database. In this post, we explore how to leverage the pgTAP extension for unit testing on Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL-Compatible Edition database, helping you build robust and reliable database applications.