![]() ![]() One key component of AWS DMS is the Schema Conversion Tool (SCT) which automatically converts the source database schema, and the majority of database code objects to a format compatible with the target database. It utilizes an automation-first approach to minimize manual processes and supports multiple homogeneous and heterogeneous migration types. Optimizing AWS DMSĪWS DMS is the native Amazon Web Services (AWS) database migration tool, allowing migration of databases quickly and securely. Fujitsu is also a member of the AWS Managed Service Provider (MSP) and Well-Architected partner programs. I’ll include end-to-end considerations, how to align database architecture with adapting business operations, and tips for approaching the inevitable manual steps of a database migration.įujitsu is an AWS Advanced Tier Services Partner with Competencies in Migration and DevOps consulting. In addition, this post highlights further considerations and wider topics concerning database migration. ![]() I will focus on optimization of the migration tool, as well as understanding the limitations and best use cases for it. These insights are drawn primarily from Oracle-to-PostgreSQL migrations delivered by Fujitsu. This post discusses some of the key learnings and experiences Fujitsuhas gained through its use of AWS Database Migration Service (AWS DMS) during database migration projects. ![]() One of the critical decisions is the choice of tooling to deliver the migration, and how to get the best out of the selected tool. There are many aspects of the end-to-end journey of migration-from discovery, assessment, management, and the migration itself. Migrating a company’s database architecture from an on-premises database to the cloud can be a complicated and time-consuming process. By Ben Brunswick, Cloud Engineer – Fujitsu ![]()
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