Author: Amit Arora

Data validation is an important process during data migrations, helping to verify that the migrated data matches the source data. In this post, we present alternatives you can use for data validation when dealing with tables that lack primary keys. We discuss alternative approaches, best practices, and potential solutions to make sure that your data migration process remains thorough and reliable, even in the absence of traditional primary key-based validation methods. Specifically, we demonstrate how to perform data validation after a full load migration from SQL Server to Amazon Aurora PostgreSQL-Compatible Edition using the PostgreSQL tds_fdw extension.

Planning a migration journey with extensive on-premises database and analytics resources have many requirements such as including time to generate a migration plan and expertise in compiling inventory, designing a migration strategy, and finalizing migration targets. Transition to AWS became remarkably streamlined with AWS DMS Fleet Advisor service. AWS DMS Fleet Advisor helps you construct […]

Many AWS customers are starting to modernize architectures and move toward open-source databases. Babelfish for Aurora PostgreSQL makes it easier to migrate applications from SQL Server to Amazon Aurora PostgreSQL-Compatible Edition. With Babelfish, Aurora PostgreSQL-Compatible supports commonly used T-SQL language and semantics, which reduces the amount of code changes related to database calls in an […]