Category: AWS Schema Conversion Tool

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. An important part of AWS SCT is the report that it […]

AWS Schema Conversion Tool (AWS SCT) is a service that allows you to migrate heterogeneous databases by converting your existing database schema from one supported database engine to another. This tool has a functionality called assessment reporting. Based on the source and target database engines you choose and the object attributes in your source schema, […]

Migrating your database from IBM Db2 LUW to Amazon Relational Database Service (Amazon RDS) for MySQL, Amazon RDS for MariaDB, or Amazon Aurora MySQL-Compatible Edition is a complex, multistage process, which usually includes assessment, database schema conversion, data migration, functional testing, performance tuning, and many other steps spanning across the stages. You can use AWS […]

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 […]