Introduction
Liquibase is an open-source database schema change management tool that enables teams to track, version, and deploy database changes easily and consistently. By utilizing migration scripts called “changesets,” Liquibase allows developers to manage schema updates, rollbacks, and track database changes across environments. Liquibase is widely used for database migrations because it supports multiple database types and integrates seamlessly into CI/CD pipelines, making it an essential tool for database version control.
Why this framework matters in your data stack
Liquibase migrations sit at the core of schema change management. Any upstream change can move through the entire data pipeline. A renamed or removed column can break dashboards, machine-learning models, or analytics workflows. Teams need early visibility into these changes to prevent data-quality issues and avoid breaking downstream pipelines.
Liquibase drives schema updates across environments:
Teams update OLTP databases such as Postgres or MySQL.
ETL tools such as Fivetran or Stitch load the data into the data warehouses, like: BigQuery or Snowflake.
Transformation tools such as dbt or Matillion reshape it.
BI tools such as Looker and Tableau consume the final datasets.
How Foundational analyzes this framework
Foundational’s Code Engine analyzes Liquibase migrations directly from the code repository. It parses migration files to extract schema definitions and identify structural changes. The system detects modifications during development or while a Pull Request remains open. This early insight allows teams to understand the downstream impact of each change before deployment and avoid unexpected issues in production.
Foundational’s process to extract schema and lineage
Foundational extracts schema and lineage from Liquibase migrations by:
Scanning and finding all Liquibase migration files.
Parsing Liquibase migration files directly from the repository.
Detecting any schema changes.
Identifying the downstream impact of each change before deployment.
By relying on the migration files, the Code Engine provides early and accurate visibility into schema and lineage changes without access to the running database. It also does not require the change to be deployed and can analyze it while the change is still pending.
Advantages of Foundational’s approach
Traditional tools extract metadata only after a migration is applied. In contrast, Foundational reads Liquibase migration scripts straight from the code repository. Foundational does not wait for schema changes to reach a live database. This approach gives teams an earlier view of schema changes and supports proactive assessment.
If the engineering team changes Liquibase files that affect the operational database in a way that may break downstream processing, Foundational detects the potential issue and alerts both the engineering team and the data engineering team. They can prevent the breaking change by fixing the issue or by updating downstream consumers so they can handle the new structure.
Sample Liquibase definitions
Set up Liquibase lineage in Foundational
Setup is simple. Connect the repository that contains your Liquibase migration files. Foundational scans for Liquibase changesets in XML, YAML, JSON, or SQL formats and identifies the relevant migration scripts automatically. It parses these files safely, extracts schema information from the code, detects changes in Pull Requests, and evaluates downstream impact.
To connect to your source control, check out the relevant How-to article from the Help Center Connectors and Integrations category.
No additional configuration is required.