With public cloud providers offering purpose-built database technology at scale for supporting cloud-based applications, a logical move for your organization is to consider breaking free from commercial database technology and migrate to open source based cloud-native databases. While this is an important consideration, the database migration is complex and needs a thorough assessment of your applications to define a successful migration roadmap. Business, IT, Application, and Database teams need an efficient migration factory model for large scale migration that minimizes the risk of migration and disruption to the business.

The database migration primarily constituted by six significant aspects:

Licensing

Complex, multi-year licensing commitments can introduce additive short-term cost or complexity into a migration effort.

Logic

Migrating database engines require rebuilding or refactoring large amounts of embedded, usually legacy business logic. Migrating database engines may also involve refactoring application code that can be a legacy code structures to modern APIs.

Data

Migrating substantial quantities of data (10–100’s of TB or more) often requires the use of specialized hardware and tools.

Purpose-Fit Database Architecture

Re-architect your applications to choose and implement the right database type based on the purpose to reap the benefits of modern database architectures.

Security and Compliance

Security and compliance are essential for industries that necessitate deploying various security controls and protection methods that include — but are not limited to — data tokenization and encryption.

Performance requirements

Data may need to travel over a remote network, and that may require refactoring of code to meet application-specific performance needs.

Before diving into a large-scale migration plan, a good starting point is to understand your TCO, ROI, migration path, and right grouping of your applications and databases.

You can begin with pilot migrations to identify the right tools, automate migration tasks, define a learning-driven factory model, and post-migration operating model in the cloud. This factory model and knowledge will allow you to maximize your migration gains and better understand the level of effort and time commitment to support massive migration efforts.

While these topics can apply to any database engines, let’s dive into a use case for migration from MS SQL server on-premises to PostgreSQL on AWS in the next blog.

Co-author: Lindsay Scarangello