AWS Database Blog

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports X2iedn powered by third-generation Intel Xeon Scalable processors built on the AWS Nitro System and featuring the third-generation Intel Xeon Scalable (Ice Lake) processors. SQL Server workloads are highly dependent on memory. As a result, memory-optimized Amazon Elastic Compute Cloud (Amazon EC2) instances are most commonly used by customers.

In this post, we discuss how to perform aggregations on a DynamoDB table using Amazon DynamoDB Streams and AWS Lambda. The content includes a reference architecture, a step-by-step guide on enabling DynamoDB Streams for a table, sample code for implementing the solution within a scenario, and an accompanying AWS CloudFormation template for easy deployment and testing.

In this post, we show you how you can use the RMAN XTTS functionality to migrate from an Oracle database hosted on Amazon Elastic Compute CLoud (Amazon EC2) to Amazon RDS for Oracle. Combined with Amazon Elastic File System (Amazon EFS) integration, XTTS can help reduce the complexity of your migration strategy, reduce the number and copies of data and backups required (as well as associated storage space consumption), and reduce the application downtime associated with completing the migration of your data.

In this post, we discuss an automotive manufacturing information management use case where we store information about components within a vehicle as well as the hierarchy between each of the components. For our automotive use case, we use Amazon DynamoDB to deliver transactional queries, such as component attribute lookups. We will also show you how to use DynamoDB for larger responses such as a recursive query for all the components in a vehicle. While recursive object relationships can be represented in graph databases and possibly traditional RDBMS (with complex joins), these deeper queries can also be represented in DynamoDB.

In this post, we demonstrate how to use the DBMS_CLOUD package to transfer files between S3 buckets and directories in an RDS Custom for Oracle database. We also show how you can access data from Amazon S3 directly using Oracle features such as external tables and hybrid partition tables. The features provided by DBMS_CLOUD could vary between different Oracle releases, so pay close attention to the steps in the post and make sure you reference DBMS_CLOUD in the Oracle Database 19c documentation. To avoid confusion, the option discussed in this post is for RDS Custom for Oracle, not for RDS for Oracle. RDS for Oracle offers S3 integration.

According to the United States Census Bureau, over 7.9 million Americans moved from one state to another in 2021 alone. One of the tasks an individual must complete when moving from state to state is trading in their driver’s license from their former state of residence for a license in their new state of residence. Each state’s Department of Motor Vehicles (DMV) is responsible for the issuance and management of driver’s licenses within the state, and this requires collaboration with other state DMVs to gather important data such as traffic offenses occurring out of state. In this post, we discuss how blockchain can streamline driver’s license issuance and foster deeper collaboration between DMVs in all 50 states and why blockchain is a compelling technology choice.

Cosmos is a decentralized network of interoperable blockchain networks that serves as an open and highly scalable environment on which to build blockchain applications. With effective support for cross-chain interaction between homogeneous and heterogeneous blockchains, Cosmos aims to extend interoperability to a broader landscape. In this post, we discuss the value and technical architecture of Cosmos and provide a detailed tutorial on the quick deployment of the Cosmos enterprise framework (IRITA) within the AWS environment.

This is a two-part series. In this post, we explain three archival solutions that allow you to archive Oracle data into Amazon Simple Storage Service (Amazon S3). In Part 2 of this series, we explain three archival solutions using native Oracle products and utilities. All of these options allow you to join current Oracle data with archived data.

This post is a continuation of Archival solutions for Oracle database workloads in AWS: Part 1. Part 1 explains three archival solutions that allow you to archive Oracle data into Amazon Simple Storage Service (Amazon S3). In this post, we explain three archival solutions using native Oracle products and utilities.

Amazon Timestream is a fast, scalable, and serverless time-series database service that makes it easier to store and analyze trillions of events per day. In this post, we guide you through the essential concepts of Timestream and demonstrate how to use them to make critical data modeling decisions. We walk you through how data modeling helps for query performance and cost-effective usage. We explore a practical example of modeling video streaming data, showcasing how these concepts are applied and the resulting benefits. Lastly, we provide more best practices that directly or indirectly relate to data modeling.