AWS Database Blog

Tag: Aurora PostgreSQL

Dive into new functionality for PostgreSQL 11

In this post, I take a close look at three exciting features in PostgreSQL 11: partitioning, parallelism, and just-in-time (JIT) compilation. I explore the evolution of these features across multiple PostgreSQL versions. I also cover the benefits that PostgreSQL 11 offers, and show practical examples to point out how to adapt these features to your applications.

Read More

Working with RDS and Aurora PostgreSQL logs: Part 2

The first post in this series, Working with RDS and Aurora PostgreSQL Logs: Part 1, discussed the importance of PostgreSQL logs and how to tune various parameters to capture more database activity details. PostgreSQL logs provide useful information when troubleshooting database issues. This post focuses on different methods to access PostgreSQL logs. The PostgreSQL logs […]

Read More

Working with RDS and Aurora PostgreSQL logs: Part 1

PostgreSQL is one of the most popular open-source relational database systems. With 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 provides two managed PostgreSQL options: Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL. One […]

Read More

Sending notifications from Amazon Aurora PostgreSQL

Enterprise customers execute many day-to-day batch jobs on Amazon Aurora PostgreSQL databases, and need notification methods such as email or text after completing such jobs to keep track of their activity. Because Aurora PostgreSQL is a managed service, it restricts access to database extensions such as pgsmtp and pgplpythonu for security reasons. This raises the […]

Read More

Validating database objects after migration using AWS SCT and AWS DMS

Database migration can be a complicated task. It presents all the challenges of changing your software platform, understanding source data complexity, data loss checks, thoroughly testing existing functionality, comparing application performance, and validating your data. AWS provides several tools and services that provide a pre-migration checklist and migration assessments. You can use the AWS Schema […]

Read More

Reducing Aurora PostgreSQL storage I/O costs

Cost reduction is one of the biggest drivers for many IT departments to explore migration of on-premises workloads to the cloud. This post shares experiences in cost management, with a focus on Amazon Aurora PostgreSQL tuning. History I recently had the privilege of leading the implementation of our Auto Telematics Application in AWS. To provide […]

Read More

Optimizing and tuning queries in Amazon RDS PostgreSQL based on native and external tools

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. PostgreSQL is considered to be the primary open-source database choice when migrating from […]

Read More

Best practices for Amazon RDS PostgreSQL replication

Amazon RDS for PostgreSQL enables you to easily configure replicas of your source PostgreSQL instance to clear your read load and to create disaster recovery (DR) resources. You can configure Read Replicas within the same Region as the source or in a different Region. When you use an RDS PostgreSQL Read Replica instance, you both […]

Read More

Use cases for query plan management in Amazon Aurora PostgreSQL

This blog post is the second in a series. The previous blog post talks about the need for the stable, consistent database performance amid changes that otherwise can cause regression on execution plans of the SQL statements. It also demonstrates how query plan management (QPM) for Amazon Aurora with PostgreSQL compatibility helps you overcome plan […]

Read More

Introduction to Aurora PostgreSQL Query Plan Management

Like all AWS services, the roadmap for Amazon Aurora PostgreSQL is driven mostly by customer feedback and requests for product enhancement. The feedback from several enterprise customers who have migrated their databases from Oracle and Microsoft SQL Server to Amazon Aurora suggests two things. Enterprises that run their database workloads for critical applications require optimal […]

Read More