Category: PostgreSQL compatible

This post is a follow-up to How Zendesk tripled performance by moving a legacy system onto Amazon Aurora and Amazon Redshift. In this post, we go over the techniques we used to plan and upgrade major versions of Aurora PostgreSQL databases for Zendesk Explore with minimal customer downtime. We also discuss the performance optimizations we performed, the cost savings we achieved, and how we accomplished all of this within a period of 6 months. AWS Technical Account Managers played a significant role in helping us achieve these goals in a short period of time. The upgrade was performed successfully and without customer downtime.

In this post, we discuss more PostgreSQL key concepts, including simple query protocol, explain plans, how to read explain plans, and tools to visualize these plans in Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL-Compatible Edition.

Customers migrating Oracle databases to Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL might encounter the challenge of scheduling jobs that require precise sub-minute scheduling to avoid workflow disruptions and maintain business operations. In this post, we demonstrate how you can use Trusted Language Extensions (TLEs) for PostgreSQL to install and use pg_dbms_job on Amazon Aurora and Amazon RDS. pg_dbms_jobs allows you to manage scheduled sub-minute jobs.

Some customers use Oracle UTL_HTTP package to write PL/SQL programs that communicate with web (HTTP) servers and invoke third-party APIs. When migrating to Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL, these customers need to perform a custom conversion of their SQL code since PostgreSQL does not offer a similar […]

In this post, we demonstrate a process for migrating an Amazon QLDB ledger into Amazon Aurora PostgreSQL using the US Department of Motor Vehicles (DMV) sample ledger from the tutorial in the Amazon QLDB Developer Guide as an example. You may use this solution as a foundation for your own migration, altering it as necessary for your schema and migration strategy.

In this post, we discuss how to use Amazon Aurora PostgreSQL-Compatible Edition as an alternative to Amazon QLDB for auditing and what features of Amazon Aurora PostgreSQL can replace some of the unique capabilities offered by Amazon QLDB.

In this post, we discuss other native indexes supported in Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL, including GIN, GiST, HASH, and BRIN, and their use cases.

In this series of posts, we discuss index types supported in Amazon Aurora PostgreSQL-Compatible edition and Amazon Relational Database Service (Amazon RDS) for PostgreSQL and their use cases. In this post, we discuss the native B-tree index and its variations.

In this post, we explore the key factors to consider when selecting a database for your generative AI applications. We focus on high-level considerations and service characteristics that are relevant to fully managed databases with vector search capabilities currently available on AWS. We examine how these databases differ in terms of their behavior and performance, and provide guidance on how to make an informed decision based on your specific requirements.

In this post, we explore the new features in PostgreSQL 16 and discuss how they improve performance and query speed. This includes new replication features, including logical decoding on standbys and parallel application of logical replication, SQL/JSON functionality, new monitoring tools, such as the pg_stat_io system view, and security features.