AWS Database Blog

Customers may prefer to host their Oracle database workloads in a managed service such as Amazon Relational Database Service (Amazon RDS) for Oracle because of the benefits offered by managed services. However, there could be workloads that have dependencies on Oracle features that aren’t supported by Amazon RDS for Oracle. For example, the flashback database […]

Your Amazon DynamoDB table might store millions, billions, or even trillions of items. If you ever need to perform a bulk update action against items in a large table, it’s important to consider the cost. In this post, I show you three techniques for cost-effective in-place bulk processing with DynamoDB. Characteristics of bulk processing You […]

When you migrate Microsoft SQL Server workloads to AWS, you might want to automate migration and minimize changes to existing applications, but still use a cost-effective option without commercial licenses and reduce operational overhead. For example, SQL Server workloads often use SQL Server Integration Services (SSIS) to extract, transform, and load (ETL) data. In this […]

Twilio is a customer engagement platform that drives real-time, personalized experiences for leading brands. Twilio has democratized communications channels like voice, text, chat, and video by virtualizing the world’s telecommunications infrastructure through APIs that are simple enough for any developer to use, yet robust enough to power the world’s most demanding applications. Twilio supports an […]

Graph databases are uniquely designed to address query patterns focused on relationships within a given dataset. From a relational database perspective, graph traversals can be represented as a series of table joins, or recursive common table expressions (CTEs). Not only are these types of SQL query patterns computationally expensive and complex to write (especially for […]

Graph databases are uniquely designed to address query patterns focused on relationships within a given dataset. From a relational database perspective, graph traversals can be represented as a series of table joins, or recursive common table expressions (CTEs). Not only are these types of SQL query patterns computationally expensive and complex to write (especially for […]

Graph databases are uniquely designed to address query patterns focused on relationships within a given dataset. From a relational database perspective, graph traversals can be represented as a series of table joins, or recursive common table expressions (CTEs). Not only are these types of SQL query patterns computationally expensive and complex to write (especially for […]

Babelfish for Aurora PostgreSQL is a capability for Amazon Aurora PostgreSQL-Compatible Edition that enables Amazon Aurora to understand commands from applications written for Microsoft SQL Server. When migrating from SQL Server to Babelfish for Aurora PostgreSQL, the first step is often a feasibility and compatibility assessment. You can use the Babelfish Compass tool to generate […]

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 […]

Over the last few years, organizations have started adopting a cloud first strategy, and we are seeing enterprises migrate their mission-critical applications, along with their data platforms, to the cloud. Occasionally, organizations need guidance in selecting the right service and solution in the cloud, along with an approach to assist with the migration. In this […]