3 posts tagged with "devops"

Snowflake's cloud data platform has transformed data warehousing, yet many teams still manage schema changes using manually-composed SQL scripts and verification processes. As data teams grow and pipelines become more complex, these approaches often become more challenging to maintain and much riskier to use.

Schema changes in production environments can quickly lead to unexpected behavior and inconsistent data, and having more contributors increases the risk of human error leading to costly downtime or data integrity issues. These cases are familiar to many data teams because the traditional manual database deployment methods come with implicit risks.

To address these challenges, Snowflake teams have begun adopting tools to automate schema changes, enforce safety checks, and ensure consistent deployments across environments.

In this post, we will compare three popular Snowflake schema management tools – Atlas, schemachange, and SnowDDL – and guide you in building reliable CI/CD pipelines to deploy schema changes with more confidence and control.

The Evolution of Database Schema Management​

In today's world, where software is developed and deployed at a rapid pace, selecting the right tools for your team is crucial. The right tools can help you move faster, be more productive, and reduce the risk of errors and bugs. Most backend applications are backed by a database, and maintaining the database schema is a critical part of the development process.

Our industry has seen many trends in the way database schemas evolve over the years. In the early days, DBAs would manually run SQL DDL commands directly against the database through a terminal. Then came GUI based, point-and-click database management tools that included schema editing capabilities.

In the early 2000s, we saw the rise of "database migration tools" that allowed developers to write versioned database upgrade scripts (usually in SQL), called "migrations", that would be executed by the tool itself. This trend was further intensified with the rise of DevOps and CI/CD, as it became the de-facto standard way for automating database schema management.

As applications evolve, database schema changes become inevitable. However, some types of changes can break the contract between the backend server and the database, leading to errors during deployment and application downtime. Ensuring that these breaking changes are detected and prevented is crucial for maintaining system stability and delivering a seamless user experience. In this post, we will explore how Atlas can help you prevent breaking schema changes from impacting your application.