Category: DMS Schema Conversion

AWS recently announced virtual target mode in AWS Database Migration Service (AWS DMS) Schema Conversion. This feature helps you start migration planning without provisioning target databases. In this post, we show you how to get started using virtual target mode in AWS DMS Schema Conversion.

In this post, we demonstrate how to use DMS Schema Conversion to assess an Amazon RDS for SQL Server database and convert it to Amazon Aurora PostgreSQL-Compatible Edition. We walk you through how to automate the setup and configuration of DMS Schema Conversion components, generate an assessment report, convert database storage and code objects, export the converted code to Amazon S3, and apply the converted code to the target database.

Organizations are increasingly seeking to modernize their database infrastructure by migrating from legacy database engines such as Microsoft SQL Server and Oracle to more cost-effective and scalable open source alternatives such as PostgreSQL. This transition not only reduces licensing costs but also unlocks the flexibility and innovation offered by PostgreSQL’s rich feature set. In this post, we demonstrate how to convert and test database code from Microsoft SQL Server and Oracle to PostgreSQL using the generative AI capabilities of Amazon Bedrock.

Today, we’re excited to inform you about a new generative AI feature in DMS SC. You can now use advanced language models to streamline and enhance your migration workflow. In this post, we discuss the key capabilities of DMS SC with generative AI and how to enable it to offer you additional recommendations to reduce manual conversion effort and time.