Database versioning is the process of tracking and managing the changes made to a database schema over time. It is essential for ensuring the consistency, reliability, and compatibility of the data and the applications that use it. In this article, you will learn some of the best practices for database versioning, such as:
A version control system (VCS) is a tool that records the history of changes made to files and folders, such as code, configuration, and documentation. It allows you to revert, merge, and compare different versions of your files. You can also use a VCS to manage your database schema changes, by storing the scripts that create, modify, or drop database objects. This way, you can track the evolution of your database schema, as well as the dependencies and relationships between the objects.
All changes should be scripted including stored procedures, schema changes triggers, etc. Automate deployment with tools from Quest like Toad or Foglight. Backup and test recoverability. Documents!
Instead of making large and complex changes to your database schema at once, it is better to apply them incrementally, using small and simple scripts that perform one task at a time. This makes it easier to test, review, and deploy your changes, as well as to roll them back if needed. You can use a naming convention to organize and order your scripts, such as prefixing them with a timestamp, a sequence number, or a version number.
To avoid human errors and ensure consistency across different environments, you should automate the deployment process of your database schema changes. You can use a tool that compares the current state of your database with the desired state defined by your scripts, and generates and executes the necessary commands to synchronize them. Alternatively, you can use a tool that runs your scripts in a predefined order, and records the versions that have been applied to your database.
To improve the communication and collaboration among the developers, testers, and administrators involved in the database development process, you should document the changes that you make to your database schema. You can use comments, annotations, or metadata to describe the purpose, functionality, and impact of your changes. You can also use a changelog file to summarize the changes that have been made in each version of your database schema, and link them to the corresponding scripts and issues.
Before deploying your database schema changes to the production environment, you should test them thoroughly in a separate environment that mimics the production one as closely as possible. You should verify that your changes do not break the existing functionality, data integrity, or performance of your database and the applications that use it. You should also test the rollback scenarios, in case you need to undo your changes in an emergency situation.
As a final precaution, you should always backup your data before applying any database schema changes to the production environment. This way, you can restore your data in case something goes wrong during the deployment process, or if you discover a serious bug or issue after the deployment. You should also backup your data regularly, and store it in a secure and accessible location.
Tools from Quest, EMC and Rubrik work well for all databases. I'll share my 20 years experience here. Veritas has tools for backup and LiteSpeed is best for SQL recovery
I'd be glad to share what clients like AIG, Goodyear and Sherwin Williams do in this space. There are so many ways to approach these topics. A project plan is needed, but don't wait to get started!