Category: AWS Schema Conversion Tool

This post demonstrates how to use AWS SCT to simplify and accelerate the migration of embedded Oracle SQL code within Java applications to PostgreSQL-compatible syntax. The solution focuses on a practical use case involving a source Oracle database coupled with a sample Java application containing numerous Oracle-specific SQL statements. By using AWS SCT, developers can automate much of the schema and SQL conversion process, reducing manual effort and minimizing errors during migration.

AWS Schema Conversion Tool (AWS SCT) makes self-managed data warehouse migrations predictable by assessing and converting the source database schema and code objects to a format compatible with Amazon Redshift. In this post, we describe how to perform a database assessment and conversion from Teradata to Amazon Redshift. To accomplish this, we use the AWS SCT and its CLI, because it provides support for Teradata as a source database, complementing the wide range of assessments handled by AWS Database Migration Service (AWS DMS) Schema Conversion (DMS SC).

This post is co-authored with Eric Boyer and Maria Hristova of Firmex. Firmex is a leading Virtual Data Room provider with more than 20,000 new rooms opened every year. In this post, we discuss how and why Firmex migrated 65,000 databases heterogeneously from their on-premises SQL Server to Amazon Aurora PostgreSQL-Compatible Edition.

Many organizations are often seeking to migrate from their commercial relational databases, such as Oracle, to open-source databases like PostgreSQL. When migrating from Oracle to PostgreSQL databases, the most time-consuming and complex part is converting database structures, code, and storage objects such as packages, procedures, functions, and triggers. Converting or modernizing from Oracle to Amazon […]

In the post, Validate database objects post-migration from Microsoft SQL Server to Amazon RDS for PostgreSQL and Amazon Aurora PostgreSQL, we explained the manual process to run relevant queries at source and target and match the output to identify the gaps post-migration. Because it’s a tedious job to validate all the available database objects, table […]

In this post, we provide an overview of database migration from IBM Db2 LUW to Amazon Aurora PostgreSQL-Compatible Edition or Amazon Relational Database Service (Amazon RDS) for PostgreSQL. We discuss the challenges you may encounter during schema conversions, and how to perform data migration using the native EXPORT and COPY commands. Additionally, we address how […]

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 […]

You can now use AWS Schema Conversion Tool (AWS SCT) to streamline a migration project from Db2 for z/OS (v12) to Amazon Relation Database Services (Amazon RDS). The list of supported targets for this source in AWS SCT is: Amazon Relational Database Service (Amazon RDS) for MySQL Amazon Aurora MySQL-Compatible Edition Amazon Relational Database Service […]

The AWS Schema Conversion Tool (AWS SCT) makes heterogeneous database migrations predictable by automatically converting the source database schema and a majority of the database code objects, including views, stored procedures, and functions, to a format compatible with the target database. An important part of the AWS SCT is the assessment reports to help you […]

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, […]