Model Relational Data In Firestore No SQL

Definitions

Documents are like JSON objects.

Collections are containers to hold multiple documents and nested collections.

Best practice: Collections should be large; documents should be small (1MB or smaller).

3 Ways of Modeling Data

3 ways to model data:

1. Root collection: collection of documents at root of database

2. Embed data directly into documents: add strings, booleans, numbers, etc.

3. Nest sub-collections onto documents: scopes collections into documents

Embedding data

If you anticipate that your documents could get very large (due to a large data set), embedding data directly into documents isn't ideal. In this case, you want to opt for a sub-collection.

When to use: You have a small data structure that doesn't need to scale up to 1000s of records.

Sub-collections

Because sub-collections are scoped to that specific user, you can't query across parents. For example, if each user has a sub-collection containing address details, sub-collections don't allow you to make queries like, "give me all users living in Ontario".

In this case, the best solution is to denormalize address at the root collection and give it the user ID for reference (kind of like a foreign key).

Creating one-to-many relationship

The pattern of using a foreign key is basically how you create a one-to-many relationship!

Creating many-to-many relationship

Hearts in Twitter are a great example of many-to-many: users have many hearts, and tweets have many hearts too.

The solution is to create the equivalent of a join table:

1. Create hearts collection.

2. In each document, the ID is userId_tweetId, creating a unique key for that relationship.

3. Each document has userId and tweetId as properties.

Note: This is very similar to an intermediate table, which is used for joins in SQL.

Best practice: Because it's expensive to get a heart count by referencing hearts directly, you usually will aggregate data by adding a heart count to your tweets.