DataOps and CI/CD with respect to database schema compare and change deployment is a critical task, mainly when it comes to databases such as Snowflake, Redshift, or Azure.
Most companies’ data landscapes include development, QA, and production database instances. Data engineers move database changes from a lower database instance to a higher database instance i.e from development to QA or QA to production database instance.
On the surface moving database objects from lower to higher instances look simple, but this is not the case when changes are complex or when multiple developers located in multiple locations develop in the same database.
Things become even worse when companies adopt an agile development process that requires frequent database changes and production moves. With the onset of cloud databases such as Snowflake, Synapse, and Redshift demand to move changes to production more frequently is becoming a common trend.
Moving changes from dev to QA or QA to prod without any automated tool is labor-intensive, error-prone, and not repetitive. Without a proper automated solution, many times teams create ad hoc queries and extraction programs to move objects from dev to QA to prod. However, a solution like 4DAlert’s schema automates the process end to end.
Let’s look at how an automated schema comparison tool such as 4DAlert saves time, helps deploy database changes with Zero error, and integrates with your DevOps and CI/CD process to automate the deployment process end to end.
4DAlert automated solution is database agnostic. It seamlessly connects with Snowflake, Redshift, Synapse, Postgres, Oracle, SQL Server, Postgres, etc, and tracks the database changes for all databases.
Data engineers manage version control of their code in the feature branch until ready to push to develop branch and beyond
As data engineers work on database changes, from time to time they would want to maintain a version of their code in a source control tool such as GIT, GitLab, GitBucket, etc. In absence of an automated process, engineers would manually extract code to a text file and then push the code to git. In this process, they spend valuable time doing non-valuable work. Many times they miss objects and therefore lose the opportunity to maintain versions for those objects.
Once data engineers in any particular work stream finish coding in their “feature” branch and are satisfied with their testing, they need to merge their code into the develop branch. At this point, data engineers need to see if there is any conflict with the develop branch and how they could resolve those conflicts.
Without an automated solution, the engineers try to use a regular text compare method, a process that is highly labor-intensive and error-prone. 4DAlert’s scheme compare and schema merge process highlight the conflicts in their version control tool and suggest an option for conflict resolution.
Deploying database changes and generating deployment scripts is not simple. Without a proper solution generating deployment scripts is a manual process. Engineers would manually go through the CREATE DDL statement of tables, views, index, and other database objects and manually create ALTER script where necessary and then deploy the script.
With an automated schema compare solution, engineers have to spend NO time creating deployment scripts. This process helps engineers to follow a repeatable process that takes zero time and is 100% error-free. 4DAlert solution goes even one step further. It highlights the DDL script (ex DROP COLUMN or DROP TABLE) that engineers should review carefully and take steps before deployment.
Many organizations have robust CI/CD processes. They want to leverage the CI/CD process to deploy database change as well. However, without a proper schema comparison tool that automatically creates deployment scripts and allows them to push deployment scripts directly into their CI/CD process, engineers manually upload the deployment scripts. This process has many manual touch points and creates opportunities for failure. An automated solution such as 4DAlert, allows engineers to generate deployment scripts and push the code to the DevOps tool used in CI/CD process. This allows them to fully automate the deployment process end to end.
In today’s collaborative environment, data engineers work from multiple locations, in multiple time zones, and on multiple projects within the same database. They follow different schedules and different project timelines. In this complex scenario, keeping all landscapes is always challenging. Without an automated solution, organizations need multiple full-time resources to keep the databases and schema in sync. An automated schema compares solution helps keep all your database schema in sync in all your environments: development, testing, performance testing, and production and enables data engineers to extract schema changes as a script to help create migration and rollback scripts.
Want to try schema compare features that will help you continuously deploy changes with Zero error? Request a demo with one of our experts at https://www.4dalert.com