Category: RDS for PostgreSQL

Indexes in PostgreSQL are essential for improving the performance of database queries. They serve as data structures that organize and optimize the retrieval of information from database tables. By creating indexes on specific columns, PostgreSQL can locate and access relevant data more efficiently. Indexes work by creating a separate data structure that contains a sorted […]

Customers are modernizing their mission-critical legacy on-premises IBM Db2 for z/OS databases to Amazon Relational Database Service (Amazon RDS) for PostgreSQL or Amazon Aurora PostgreSQL-Compatible Edition for its scalability, performance, agility, and availability. You can use the AWS Schema Conversion Tool (AWS SCT) to simplify the schema conversion from Db2 for z/OS to Amazon RDS […]

Amazon Relational Database Service (Amazon RDS) for PostgreSQL now supports trusted PL/Rust, allowing developers to safely build high-performance database functions in the Rust programming language. PL/Rust is an open-source project that lets you write Rust code that runs directly inside a PostgreSQL database, and provides support for PostgreSQL features such as running queries, writing trigger […]

AWS launched Amazon Database Migration Accelerator (Amazon DMA) to accelerate your journey to AWS Databases and Analytics services and achieve cloud adoption benefits such as cost savings and performance improvements. In this post, we share Amazon DMA’s approach to migrate generated columns to PostgreSQL implementations, such as Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL-Compatible […]

This post is a continuation of Federated query support for Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL – Part 1. To recap, in 2003, the SQL standard added a new specification called SQL/MED (SQL Management of External Data). In 2011, PostgreSQL 9.1 was released with read-only support of this standard, and PostgreSQL 9.3 added […]

Organizations across diverse sectors are exploring novel ways to enhance user experiences by harnessing the potential of Generative AI and large language models (LLMs). In the fashion industry generative AI is revolutionizing the creative process. By analyzing user preferences and data, AI algorithms can generate unique apparel patterns and designs, bringing a new level of […]

While databases are used to store and retrieve data, there are situations where applications should archive or purge the data to reduce storage costs or improve performance. However, there are often business requirements where an application must query both active data and archived data simultaneously. Developers need a solution that lets them benefit from using […]

Many customers use AWS Backup to automatically create Amazon Relational Database Service (Amazon RDS and Aurora) database snapshots. RDS database snapshots are a convenient way to protect your data and make it easy to recover in the event of an accident or disaster. If you’re using RDS Snapshots for long-term archival to meet compliance requirements […]

AWS launched Amazon Database Migration Accelerator (Amazon DMA) to accelerate your journey to AWS databases and analytics services and achieve cloud adoption benefits such as cost savings and performance improvements. Amazon DMA has assisted thousands of customers globally to migrate their workloads (database and application) to AWS databases and analytics services. In this post, we […]

To migrate an Oracle database to Amazon Aurora PostgreSQL-Compatible Edition, you usually need to perform both automated and manual tasks. The automated tasks include schema conversion and data migration, which can be handled with the AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS), respectively. The manual tasks involve post-schema AWS […]