Category: Amazon Aurora

Amazon Relational Database Service (Amazon RDS) and Amazon Aurora support a multitude of instance types for you to scale your database workloads based on your needs (see Amazon RDS DB instance classes and Aurora DB instance classes, respectively). In 2020, AWS announced Amazon M6g and R6g instance types for Amazon RDS and recently announced the […]

You may have stringent regulatory compliance obligations that require an effective multi-Region disaster recovery (DR) plan to mitigate a Region-wide disaster. AWS offers multiple methods to meet these needs, taking into consideration different factors such as recovery time objective (RTO), recovery point objective (RPO), and costs. In this post, I focus on how to keep […]

Critical workloads with a global footprint have strict availability requirements and may need to tolerate a Region-wide outage. Traditionally, this required a difficult trade-off between performance, availability, cost, and data integrity, and sometimes required a considerable re-engineering effort. Due to high implementation and infrastructure costs that are involved, some businesses are compelled to tier their […]

Amazon Aurora is a relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost effectiveness of open-source databases. Aurora has a distributed architecture that replicates a shared storage volume across three Availability Zones to provide a high availability solution with no data loss and failover time measured […]

The database refresh process consists of recreating of a target database using a consistent data copy of a source database, usually done for test and development purposes. Fully-managed database solutions such as Amazon Relational Database Service (Amazon RDS) or Amazon Aurora make it incredibly easy to do that. However, database administrators may need to run […]

Organizations that store and process data in relational databases are making the shift to the cloud. As part of this shift, they often wish to modernize their application architectures and add new cloud-based capabilities. Chief among these are machine learning (ML)-based predictions such as product recommendations and fraud detection. The rich customer data available in […]

You’re moving your applications to the AWS Cloud and you want to migrate from a commercial database engine to an open source database. One thought that may have rightfully crossed your mind is that changing database engines is not a simple task. Rather, it can be a complex, multi-step process that involves pre-migration assessments, converting […]

When designing many applications today, developers rightfully think of the end-user first and focus on what the experience will be. How the data is ultimately stored is an implementation detail that comes later. Combined with rapid release cycles, “schema-less” database designs fit well, allowing for flexibility as the application changes. PostgreSQL natively supports this type […]

Organizations improve security and tracing postures by going through database audits to check that they’re following and provisioning well-architected frameworks. Security teams and database administrators often perform in-depth analysis of access and modification patterns against data or meta-data in their databases. During auditing, you may raise the following questions: Who accessed or modified the data? […]

Migrating from commercial databases to open source is a multistage process with different technologies, starting from assessment, data migration, data validation, and cutover. One of the key aspects for any heterogenous database migration is data type conversion. In this post, we show you a step-by-step approach to migrate user-defined types (UDT) from Oracle to Amazon […]