Introduction
TypeORM is an Object-Relational Mapping (ORM) tool for TypeScript and JavaScript. The tool:
Helps developers work with databases in a more intuitive way.
Lets teams define a database schema using models that map directly to tables.
Allows CRUD operations (Create, Read, Update, Delete) through TypeScript or JavaScript methods instead of raw SQL.
Supports multiple databases, including MySQL, PostgreSQL, MariaDB, and SQLite.
This flexibility, combined with strong typing, makes TypeORM a common choice for building reliable and scalable applications in the Node.js ecosystem.
Why this framework matters in your data stack
TypeORM is a key part of many application stacks and manages operational databases in OLTP environments. These databases often feed into wider data pipelines. ETL tools such as Fivetran or Airbyte move this data into warehouses like Snowflake or BigQuery.
TypeORM models define the database schema. Any change to these models can affect the entire data pipeline. For example:
Updates to column names
Changes to data types
Removal of columns
Modifications to relationships or structure
These updates can disrupt downstream processes, including transformations and dashboards. Teams that rely on this data need early visibility into such changes to avoid data quality issues and prevent unexpected breakages.
How Foundational analyzes this framework
Foundational’s Code Engine extracts schema and lineage by analyzing TypeORM models directly in the codebase. It detects changes early in development and inside pending Pull Requests. This early visibility helps teams assess downstream impact before they deploy a change.
The Code Engine:
Scans TypeORM entity files
Identifies table names, column types, and relationships
Builds schema information from the source code
Highlights changes across Pull Requests
This approach reduces risk and prevents schema changes from reaching production without proper review.
Foundational’s process to extract schema and lineage
Foundational’s Code Engine automates the extraction of schema and lineage by analyzing TypeORM models directly in the codebase. The Code Engine:
Scans TypeORM entity files and extracts schema details such as table names, column types, and relationships.
Detects schema changes early in the development cycle, including changes in pending Pull Requests.
Once the data is in a warehouse, it is transformed using tools like dbt or Matillion and consumed by BI tools like Looker or Tableau.
This early insight allows teams to evaluate downstream impact before they deploy a change, reducing the risk of disruptions in production systems.
Advantages of Founational’s approach
Traditional tools extract schema information from the database after a change is deployed. They rely on the live database as the source of truth. This delays detection and increases the risk of breaking downstream systems.
Foundational takes a different approach. It analyzes TypeORM model files directly in the codebase. This allows the Code Engine to detect schema changes early in the development cycle or inside pending Pull Requests. Early insight helps teams understand the downstream impact before they deploy a change to production.
Sample TypeORM Code
Foundational scans TypeORM entity files and extracts details such as:
Table names
Column types
Relationships
By identifying these changes directly from the source code, Foundational reduces the risk of unexpected breakages. Teams see the effect of each schema update earlier, which helps them protect downstream transformations, reports, and applications from unintended impact.
Set up TypeORM lineage in Foundational
Setup is simple. Connect the repository that contains your TypeORM entity files. Foundational detects the files, loads them safely, and extracts schema and lineage directly from the code.
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.