chinook-database VS chinook-database

In literally 30 seconds, you can open the blog post, upload a SQLite file, and then query it in the Splitgraph web console (or via HTTP, or via any Postgres client). Authentication is not required.

Here's the 30 second video [0] and end result [1]. If you don't have a SQLite file handy and want to try it yourself, here's a link to the Chinook Database [2].

[0] Video (30 seconds): https://twitter.com/splitgraph/status/1646612048837591040

[1] Repository: https://www.splitgraph.com/miles/chinook-tables/latest/-/tab...

[2] chinook.sqlite: https://github.com/lerocha/chinook-database/blob/e7e6d5f008e...

I’ll be using a Postgres datasource (the famous Chinook database) for my example, using WunderGraph to make it accessible through JSON-RPC to my Next.js frontend.

If you look at a typical SQL query in analytics, it looks something like this (taken from Chinook sample database):

schemacrawler/chinook-database builds on the earlier project. The project has an automatic build using GitHub Actions, which pulls scripts from lerocha/chinook-database, cleans them up, and converts them all to UTF-8 with consistent line-endings. Then are are repacked and redistributed in various ways - as a Java jar file for use in Java programs or in tests with database in Testcontainers. The SQLite database can be directly download from the project site. But probably the best way to use the package it is use the Docker image from schemacrawler/chinook-database to create the Chinook database on a database of your choice, whether the database server is running on a separate host or within a Docker container itself.

https://github.com/lerocha/chinook-database#:~:text=Chinook%20is%20a%20sample%20database,single%20and%20multiple%20database%20servers.

schemacrawler/chinook-database builds on the earlier project. The project has an automatic build using GitHub Actions, which pulls scripts from lerocha/chinook-database, cleans them up, and converts them all to UTF-8 with consistent line-endings. Then are are repacked and redistributed in various ways - as a Java jar file for use in Java programs or in tests with database in Testcontainers. The SQLite database can be directly download from the project site. But probably the best way to use the package it is use the Docker image from schemacrawler/chinook-database to create the Chinook database on a database of your choice, whether the database server is running on a separate host or within a Docker container itself.

Try it out. Make sure that you have Docker installed on your system, or download SchemaCrawler. Download a sample SQLite database called "chinook-database-2.0.1.sqlite" into your current directory. Create a text file called "mermaid.py" with the following contents:

The command assumes that a SQLite database called "chinook-database-2.0.1.sqlite" is in your current directory. A file called "output.png" will be generated with the database schema, including foreign key relationships. You can generate PDF files, and other types of output too. Go through the SchemaCrawler tutorials on Katacoda to learn more SchemaCrawler commands. If you are using PowerShell on Windows, replace the trailing backslash on each line with a back-tick.