This repo contains a docker-based solution to containerize and run Microsoft SQL with automated creation of schemas and tables, and population of data from CSV files. This helps with creating a predefined copy of an application's database, which can help with local development, end-to-end testing, etc. This is not a tool per se, but rather a template or a solution using existing tools like docker.

1. Install Docker Engine
2. Fork or clone this repo
3. Duplicate and rename .env.example file to .env and set all values.
4. Create and populate data folder.
   • Create data/__ddl__ folder and add all DDL statements as .sql files
   • Read the section below to understand how to populate this folder.
5. (Optional): Rename name inside docker-compose.yml to your project/app name. Default is localize-mssql.
6. Install all dependencies by running npm install
7. To create a fresh copy of all tables and data, run npm start. This will initialize the MSSQL server and run all SQL scripts and insert statements.
8. Once the tables have been populated with the test data, commit the changes to create a new image docker commit <container-id> <app-name>:<tag>.

The created image (which runs MSSQL server with preconfigured test data) can now be used across your dev and testing environments! And this solution works easily with CI too!

• Add all DDL statements inside data/__ddl__/. Prefix with a number for ordering.
  • Example: 01-fileA.sql will be executed before 02-fileB.sql
• For populating data, create a subdirectory with the schema name, and a csv file with table name.
  • Example: For a table dbo.table1, create a subdirectory dbo (inside the data folder) and a file 01-table1.csv.
  • The numbering before table name ensures the order in which to execute the files. This helps with foreign key constraints.

MSSQL image from Microsoft does not support ARM64 architecture (Apple Silicon devices will be affected). Follow this blog for a workaround. The workaround is to use Rosetta (included in Docker engine) for emulating amd64 images.

• Docker Commit
• SQL Server Docker Image