AWS Database Blog
Category: HAQM Aurora
Migrate Google Cloud SQL for PostgreSQL to HAQM RDS and HAQM Aurora using pglogical
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+.
Streamline code conversion and testing from Microsoft SQL Server and Oracle to PostgreSQL with HAQM Bedrock
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 HAQM Bedrock.
Supercharging vector search performance and relevance with pgvector 0.8.0 on HAQM Aurora PostgreSQL
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.
Connect HAQM Bedrock Agents with HAQM Aurora PostgreSQL using HAQM RDS Data API
In this post, we describe a solution to integrate generative AI applications with relational databases like HAQM Aurora PostgreSQL-Compatible Edition using RDS Data API (Data API) for simplified database interactions, HAQM Bedrock for AI model access, HAQM Bedrock Agents for task automation and HAQM Bedrock Knowledge Bases for context information retrieval.
HAQM Aurora Global Database introduces support for up to 10 secondary Regions
In this post, we dive deep into HAQM Aurora Global Database’s new support for up to 10 secondary Regions and explore use cases it unlocks. An Aurora Global Database consists of one primary Region and up to 10 read-only secondary Regions for low-latency local reads.
Achieve up to 1.7 times higher write throughput and 1.38 times better price performance with HAQM Aurora PostgreSQL on AWS Graviton4-based R8g instances
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.
Create a unit testing framework for PostgreSQL using the pgTAP extension
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 HAQM RDS for PostgreSQL and HAQM Aurora PostgreSQL-Compatible Edition database, helping you build robust and reliable database applications.
HAQM CloudWatch Database Insights applied in real scenarios
In this post, we show how you can use HAQM CloudWatch Database Insights for troubleshooting your HAQM RDS and HAQM Aurora resources. CloudWatch Database Insights serves as a database observability solution offering a tailored experience for DevOps engineers, application developers, and database administrators. This tool is designed to accelerate database troubleshooting processes and address issues across entire database fleets, enhancing overall operational efficiency.
Understanding transaction visibility in PostgreSQL clusters with read replicas
On April 29, 2025, Jepsen published a report about transaction visibility behavior in HAQM RDS for PostgreSQL Multi-AZ clusters. We appreciate Jepsen’s thorough analysis and would like to provide additional context about this behavior, which exists both in HAQM RDS and community PostgreSQL. In this post, we dive into the specifics of the issue to provide further clarity, discuss what classes of architectures it might affect, share workarounds, and highlight our ongoing commitment to improving community PostgreSQL in all areas, including correctness.
How Heroku migrated hundreds of thousands of self-managed PostgreSQL databases to HAQM Aurora
In this post, we discuss how Heroku migrated their multi-tenant PostgreSQL database fleet from self-managed PostgreSQL on HAQM Elastic Compute Cloud (HAQM EC2) to HAQM Aurora PostgreSQL-Compatible Edition. Heroku completed this migration with no customer impact, increasing platform reliability while simultaneously reducing operational burden. We dive into Heroku and their previous self-managed architecture, the new architecture, how the migration of hundreds of thousands of databases was performed, and the enhancements to the customer experience since its completion.