Data modeling best practices in Firebase - Time & Space Complexity

Time Complexity: Data modeling best practices

O(n)

Understanding Time Complexity

When designing data models in Firebase, it's important to understand how the number of operations grows as your data grows.

We want to know how the structure of data affects the speed and cost of reading and writing.

Scenario Under Consideration

Analyze the time complexity of reading user posts stored in a flat vs nested structure.

// Flat structure example
const postsRef = firebase.database().ref('posts');
postsRef.orderByChild('userId').equalTo(userId).once('value').then(snapshot => {
  // process posts
});

// Nested structure example
const userPostsRef = firebase.database().ref(`user-posts/${userId}`);
userPostsRef.once('value').then(snapshot => {
  // process posts
});

This code reads posts for a user either by querying a flat list or by reading a nested list under the user.

Identify Repeating Operations

Look at what happens repeatedly when data grows.

• Primary operation: Reading posts from the database.
• How many times: Number of posts for the user (n).

How Execution Grows With Input

As the number of posts grows, the time to read them changes depending on the data model.

Input Size (n)	Approx. Api Calls/Operations
10	10 reads in flat query, 1 read in nested
100	100 reads in flat query, 1 read in nested
1000	1000 reads in flat query, 1 read in nested

Pattern observation: Flat queries require more operations as data grows; nested reads stay constant.

Final Time Complexity

Time Complexity: O(n) for flat queries, O(1) for nested reads

This means reading data from a flat list grows linearly with the number of items, but reading from a nested path stays constant.

Common Mistake

[X] Wrong: "Storing all data in one big list is always simpler and faster."

[OK] Correct: As data grows, queries on big lists become slower and cost more, unlike nested data which can be accessed directly.

Interview Connect

Understanding how data structure affects operation cost shows you can design efficient, scalable apps in Firebase.

Self-Check

"What if we indexed the flat list by userId? How would that change the time complexity of reading posts?"

Practice

1. What is the main reason to use collections and documents in Firestore for data modeling?

easy

A. To make data read-only for all users

B. To store all data in one big JSON object

C. To avoid using any security rules

D. To organize data in a way that is easy to query and scale

Solution

1. Step 1: Understand Firestore structure

   Firestore organizes data into collections and documents to keep data structured and easy to access.

2. Step 2: Benefits of collections and documents

   This structure allows efficient queries and scaling as your app grows.

3. Final Answer:

   To organize data in a way that is easy to query and scale -> Option D

4. Quick Check:

   Firestore uses collections/documents for scalable data [OK]

Hint: Think of collections as folders and documents as files [OK]

Common Mistakes:

• Thinking all data should be in one JSON object
• Ignoring the need for security rules
• Assuming data is read-only by default

2. Which of the following is the correct way to reference a document in Firestore?

easy

A. db.users('user123')

B. db.collection('users').doc('user123')

C. db.get('users/user123')

D. db.document('users').collection('user123')

Solution

1. Step 1: Recall Firestore syntax

   Firestore uses collection() to select a collection and doc() to select a document.

2. Step 2: Check each option

   db.collection('users').doc('user123') correctly uses collection('users').doc('user123'). Others do not follow Firestore syntax.

3. Final Answer:

   db.collection('users').doc('user123') -> Option B

4. Quick Check:

   Firestore document reference uses collection().doc() [OK]

Hint: Remember: collection() then doc() for Firestore paths [OK]

Common Mistakes:

• Using incorrect method names like get() or document()
• Swapping collection and document order
• Trying to access documents directly from db without collection

3. Given this Firestore data model:

users (collection)
  user123 (document)
    name: 'Alice'
    posts (collection)
      post1 (document)
        title: 'Hello'

What will db.collection('users').doc('user123').collection('posts').get() return?

medium

A. A list of all posts documents under user123

B. An error because posts is not a field

C. Only the user123 document data

D. All users documents with their posts

Solution

1. Step 1: Understand nested collections

   In Firestore, collections can be nested under documents. Here, posts is a subcollection under user123.

2. Step 2: What does the query do?

   The query gets all documents in the posts collection under user123, so it returns all posts documents.

3. Final Answer:

   A list of all posts documents under user123 -> Option A

4. Quick Check:

   Subcollections return their documents on get() [OK]

Hint: Subcollections are accessed by chaining collection().doc().collection() [OK]

Common Mistakes:

• Thinking subcollections are fields inside documents
• Expecting get() to return parent document data
• Assuming get() returns all users and posts together

4. You have this Firestore security rule snippet:

match /users/{userId} {
  allow read, write: if request.auth.uid == userId;
}

What is the main issue if you want users to read their posts stored in a subcollection posts under their user document?

medium

A. The rule does not cover the posts subcollection, so access is denied

B. The rule allows anyone to read posts

C. The rule allows write but not read

D. The rule only works for admin users

Solution

1. Step 1: Analyze the rule scope

   The rule matches only the /users/{userId} document, not any subcollections like posts.

2. Step 2: Effect on subcollections

   Without explicit rules for /users/{userId}/posts/{postId}, access to posts is denied by default.

3. Final Answer:

   The rule does not cover the posts subcollection, so access is denied -> Option A

4. Quick Check:

   Security rules must cover subcollections explicitly [OK]

Hint: Rules must match subcollections separately to allow access [OK]

Common Mistakes:

• Assuming parent document rules apply to subcollections
• Believing rules allow all reads by default
• Confusing read and write permissions

5. You want to design a Firestore data model for a chat app where users can have many messages. Which approach follows best practices for scalability and easy querying?

hard

A. Store all messages in a single collection with a userId field to filter messages

B. Store messages as an array field inside each user document

C. Create a messages subcollection under each user document

D. Store messages in a single document with nested objects for each message

Solution

1. Step 1: Consider scalability needs

   Storing many messages inside one document or array can cause size limits and slow queries.

2. Step 2: Use subcollections for many related items

   Creating a messages subcollection under each user document allows efficient queries and scales well.

3. Final Answer:

   Create a messages subcollection under each user document -> Option C

4. Quick Check:

   Use subcollections for large, related data sets [OK]

Hint: Use subcollections for many related items to avoid document size limits [OK]

Common Mistakes:

• Putting many items in arrays inside documents
• Using one big collection without filtering
• Storing all data in one document causing size errors