Category: Advanced (300)

XA transactions are not a very familiar concept to lots of people and therefore hardly used. An XA transaction is a two-phase commit protocol that supports distributed transactions that updates multiple relational databases. It involves a transaction manager that monitors this global transaction. XA makes sure that transactional updates are committed in all of the […]

In this post, we focus on database object validation for the heterogenous migration from SAP ASE to Amazon Relational Database Service (Amazon RDS) for MySQL, Amazon RDS for MariaDB, or Amazon Aurora MySQL-Compatible Edition. For schema conversion and migration, you can use AWS Schema Conversion Tool (AWS SCT). AWS SCT helps convert your database schema […]

Organizations are looking for ways to better leverage their data to improve their business operations. With Amazon Aurora, Aurora Machine Learning, and Amazon SageMaker, you can train machine learning (ML) services quickly and directly integrate the ML model with your existing Aurora data to better serve your customers. In this post, we demonstrate how a […]

For manufacturers it’s important to track transformations and transfers of products as they travel through the supply chain. In the event of quality issues, the ability to quickly and accurately identify a defective product and gather data for root cause analysis and containment is critical. NXP Semiconductors has been working to improve its product traceability […]

In the first three posts of this four-part series, you learned how the choice of zonal or Regional services impacts availability, and some important characteristics of Amazon DynamoDB when used in a multi-Region context with global tables. Part 1 also covered the motivation for using multiple Regions. Part 2 discussed some important characteristics of DynamoDB. […]

In the first two posts of this four-part series, you learned how the choice of zonal or Regional services impacts availability and some important characteristics of Amazon DynamoDB when used in a multi-Region context with global tables. Part 1 also covered the motivation for using multiple AWS Regions. Part 2 discussed some important characteristics of […]

Businesses today want to enhance the data stored in their relational databases and incorporate up-to-the-minute predictions from machine learning (ML) models. However, most ML processing is done offline in separate systems, resulting in delays in receiving ML inferences for use in applications. AWS wants to make it efficient to incorporate real-time model inferences in your […]

In this post, we demonstrate how you can use AWS CloudFormation, open-source Apache JMeter, and Python to generate a performance testing framework for Amazon Aurora PostgreSQL-Compatible Edition databases. This performance testing model can help you run multiple iterations of load testing on Aurora PostgreSQL and make data-driven decisions regarding the database version, configuration, and instance […]

AWS recently added Google Cloud for MySQL as a source to AWS Data Migration Service (AWS DMS) for MySQL 8.0 and newer. In this post, we demonstrate how you can migrate from Google Cloud for MySQL to Amazon Aurora MySQL-Compatible Edition in an automated way and minimize downtime using AWS DMS. As of this writing, […]

July 2023: This post was reviewed for accuracy. Many of our customers use Amazon Relational Database Service (Amazon RDS) for SQL Server for their large mission-critical SQL Server databases. Customers have asked for the optimal solution to safeguard their large databases on Amazon RDS for SQL Server to help them meet their requirements for Recovery […]