Category: AWS Schema Conversion Tool

Database migrations typically consist of converting the database schema and loading the data from the source database to the target database. After the migration, developers still need to change the application to use the target database drivers, and they often need to rewrite the application code to make it all work. With Babelfish for Aurora […]

Database migration is a multi-step process comprised of assess, mobilize and modernize phases with different tools and technologies involved. You can use tools such as AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS) to accelerate each of these phases. In this post, we demonstrate how to use the AWS SCT […]

Many organizations are benefiting from the performance gains and ease of administration of the Amazon Aurora database platform. The idea of breaking free from commercial licenses, backup administration, and data center maintenance is always a welcome thought. But where to begin, and how complex is the journey to migrate from SQL Server to Amazon Aurora […]

Database object validation plays a key role in the database migration process. It’s the process of determining whether all the source database objects have been successfully migrated to the target database by comparing their types and counts. If you miss the validation phase, you may encounter run time errors due to missing database objects which […]

This post is part three of a series, and shows the steps to modernize a legacy SQL Server database to Amazon Aurora PostgreSQL-Compatible Edition using Babelfish. Babelfish is a capability of Amazon Aurora that allows it to understand the SQL Server dialect. In Part 1, we walked you through a step-by-step approach to re-architect a […]

The AWS Schema Conversion Tool (AWS SCT) accelerates migration for commercial database and data warehouse schemas along with code objects to open-source engines or AWS-native services, such as Amazon Aurora and Amazon Redshift. For your database migration to the cloud, you can choose a rehost (lift and shift), replatform (lift and reshape), or refactor approach. […]

Increasingly, customers are looking to break free from their legacy database (e.g., Oracle and Microsoft SQL Server) and move to a cloud-native database such as open-source engines running on AWS. One of the preferred destinations for this data is Amazon Aurora. In this post, we walk through a migration of a Microsoft Azure SQL database […]

In this post (the first in a multi-part series), we describe new capabilities to automate your schema conversion, preserve your investment in existing scripts, reports, and applications, accelerate query performance, and reduce your overall cost to migrate to Amazon Redshift. Check out all posts in this series: Accelerate your data warehouse migration to Amazon Redshift […]

July 2023: This post was reviewed for accuracy. An Oracle to PostgreSQL migration in the AWS Cloud can be a multistage process with different technologies and skills involved, starting from the assessment stage to the cutover stage. For more information about the migration process, see Database Migration—What Do You Need to Know Before You Start? […]

You’re moving your applications to the AWS Cloud and you want to migrate from a commercial database engine to an open source database. One thought that may have rightfully crossed your mind is that changing database engines is not a simple task. Rather, it can be a complex, multi-step process that involves pre-migration assessments, converting […]