Snapshot Quick Start Guide

First off, you'll need a free Snaplet account. Sign up to Snaplet Cloud (opens in a new tab).

Snaplet allows you to seed production-like data using the seed feature, or create a snapshot from an existing production database.

We'll be doing the later, so select 'Continue' to proceed with creating a snapshot.

You'll see a short overview of what the snapshot capture process entails. Click 'Let's go'.

The first step is to choose the source database you're going to connect to Snaplet. The source database is typically your production database. Click 'Provide my own db'.

If you're uncomfortable connecting to your actual production database, use your staging or QA database, or the Snaplet demo database. Supabase users should select the Supabase option and follow the Supabase tutorial for assistance.

You'll need to provide your source database connection details. You can either do so individually for each of the values, or import a connection string.

Once done, click 'Test my connection' to verify that Snaplet is able to connect to your database, and proceed. If you see a warning about read-only access to your database, make sure you're using read-only role credentials for Snaplet.

If you're having trouble getting your database connection string to work, refer to our connection string reference. Prisma also has a reference guide (opens in a new tab) on URI encoding that may be useful.

You will now be prompted to create a subset of your source database.

Subsetting is great for reducing the size of larger databases to a more managable size.

Select the starting table for your subset (typically your "primary" table, like users or customers) and select how many rows of data you'd like.

You can also opt not to subset at all by selecting 'All rows'. Select any option to proceed.

You can now transform the data from your source database.

Snaplet's transform process can scramble all data from your source database, while retaining the overall "shape" of that data, in essence removing any personally-identifiable data.

You can also not to transform the data. Select either option to proceed.

Snaplet's workers will now connect to your source database, copy the contents, and depending on what you've selected, subset and transform the data. The output of this process is a database snapshot, which you can then restore into your development environment to code against.

The snapshot capture process should finish within a few minutes for all but the biggest databases. Once it's done, you'll see a message confirming its succesful capture.

At this point, you have a database snapshot, and will need to restore this snapshot into your development environment or workflow to use it further. You can do this by installing and setting up the Snaplet CLI, and running the command to restore a snapshot.

Use your preferred installer to install and setup Snaplet. We're using npx snaplet setup here. When prompted, select 'y' to proceed.

Just like the Snaplet Cloud experience, select the option to use production data as your data source.

Provide the connection string for your target database, typically your local development environment database, but it could be any database you want to code against. This is where the snapshot will be restored to, overwriting all data in the database and replacing it with the snapshot data.

You'll be prompted whether you want to link a project from Snaplet Cloud - select yes, and select the project you created earlier as part of this quick start guide.

With the CLI associated with your Cloud project, and your target database defined, you're now ready to restore your snapshot into your database to code against.

Run snaplet snapshot restore or snaplet ss restore --latest to restore your snapshot into your target database.

You may be prompted to confirm that your snapshot will overwrite your target database if you're not using a local database.

The Snaplet CLI will provide an update to the restoration process, and notify you on completion. You can now code against your snapshot data in your target database!

You can view your database in your preferred database viewer to verify that Snaplet has successfully and safely transformed all the potentially sensitive data from your source database if you opted to transform this data earlier.