Category: Advanced (300)

In this post, we compare the high availability (HA) and disaster recovery (DR) features of Amazon Aurora to Oracle, with a focus of the Aurora disk subsystem and how this key innovation allows Amazon Aurora Global Database to deliver performance and availability. Data today is increasingly seen as a corporate asset, and safeguarding this asset is a key focus for many businesses. When that data exists in a database, the vendors of these systems produce methods […]

In Part 1 of this series, we discussed how the IDENTITY column is used in different relational database management systems. In this post, we focus on how AWS Database Migration Service (AWS DMS) handles tables with IDENTITY column. For the source database, AWS DMS captures the IDENTITY column as a regular column. For the target […]

In relational database management systems, an IDENTITY column is a column in a table that is made up of values generated automatically by the database at the time of data insertion. Although different systems handle the implementation of IDENTITY columns differently, they share some common characteristics. In most cases, the value of the IDENTITY column […]

Regular backups are a key component of designing business-critical applications to be resilient in the event of any failure situation. They provide many benefits, the most important being data protection, more efficient recovery of data in the event of disruptions, compliance with organization and legal requirements, and simplified maintenance. Point-in-time recovery (PITR) for DynamoDB provides […]

This post is a continuation of Automate benchmark tests for Amazon Aurora PostgreSQL. To recap, optimizing a database is an important activity for new and existing application workloads. You need to take cost, operations, performance, security, and reliability into consideration. Conducting benchmarks help with these considerations. With Amazon Aurora PostgreSQL-Compatible Edition, you can run multiple […]

While managing databases at scale in AWS, there are certain scenarios where you may need to maintain an Amazon Aurora cluster in a single or multiple AWS accounts. These scenarios include but are not limited to mergers and acquisitions, consolidating all accounts to use only a single account, or compliance to maintain production and development […]

This post is co-authored with Vivek Yadav from Koo. Koo is a global micro-blogging platform that allows users to share their thoughts and opinions in various languages. Launched in March 2020, the app has quickly gained immense popularity, with millions of users joining the platform to share their views and connect with like-minded individuals. In […]

Amazon DynamoDB supports transactions to give atomicity, consistency, isolation, and durability (ACID), helping you maintain data consistency in your workloads. A database transaction is a sequence of multiple operations that are performed on one or more tables. These sequences of multiple operations represent a unit of work that is committed to the tables or rolled […]

Many global corporations are managing multiple supply chains, and they depend on those operations to not only deliver goods on time but to respond to divergent customer and supplier needs. According to a McKinsey study, it’s estimated that significant disruptions to production now occur every 3.7 years on average, adding new urgency to supply chain […]

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 […]