Cost optimization (read/write reduction) in Firebase - Commands & Configuration

Introduction

Firebase charges based on how many times your app reads and writes data. Reducing these operations helps lower your bill while keeping your app fast and responsive.

When your app has many users reading the same data repeatedly.

When you want to avoid unnecessary writes that don't change data.

When you want to cache data locally to reduce network calls.

When you want to batch multiple writes into one operation.

When you want to listen only to specific data changes instead of the whole database.

Commands

This command fetches your current Firestore security rules to check if you can optimize reads by restricting access.

Terminal

firebase firestore:rules:get

Expected Output

service cloud.firestore {

  match /databases/{database}/documents {

    match /{document=**} {

      allow read, write: if false;

    }

  }

}

Deploy updated Firestore rules that limit reads and writes to only necessary data, reducing costs.

Terminal

firebase deploy --only firestore:rules

Expected Output

=== Deploying to project my-firebase-project ===



✔  firestore: rules updated successfully



✔  Deploy complete!

→

--only - Deploy only Firestore rules without affecting other services

List your Firestore indexes to ensure queries are efficient and do not cause extra reads.

Terminal

firebase firestore:indexes

Expected Output

No composite indexes defined.

Check logs of Cloud Functions that may be causing unnecessary reads or writes.

Terminal

firebase functions:log

Expected Output

2024-06-01T12:00:00.000Z myFunction: Read 10 documents

2024-06-01T12:01:00.000Z myFunction: Write 1 document

Key Concept

If you remember nothing else from this pattern, remember: reducing unnecessary reads and writes directly lowers your Firebase costs.

Common Mistakes

Reading entire collections instead of specific documents

This causes many more reads than needed, increasing costs and slowing your app.

Query only the documents you need using filters or document IDs.

Writing data on every user action without checking if data changed

Unnecessary writes increase your billing and can cause extra reads for listeners.

Check if data changed before writing, or batch writes together.

Listening to large data sets with real-time listeners when not needed

Real-time listeners keep reading data continuously, increasing costs.

Use one-time reads or limit listeners to small data subsets.

Summary

Use Firestore security rules to restrict reads and writes to only necessary data.

Query specific documents or filtered data instead of entire collections.

Check and reduce unnecessary writes by verifying data changes before saving.

Practice

1. Which practice helps reduce Firebase costs by minimizing the number of document reads?

easy

A. Use separate writes for each field update

B. Write data multiple times to ensure consistency

C. Read data once instead of using continuous listeners

D. Always overwrite entire documents on update

Solution

1. Step 1: Understand Firebase read costs

   Firebase charges for each document read. Continuous listeners keep reading data repeatedly, increasing costs.

2. Step 2: Choose cost-saving read method

   Reading data once fetches the document a single time, reducing read operations and costs.

3. Final Answer:

   Read data once instead of using continuous listeners -> Option C

4. Quick Check:

   Minimize reads = Read once [OK]

Hint: Read once, avoid continuous listeners to save costs [OK]

Common Mistakes:

• Thinking continuous listeners cost less
• Assuming multiple writes reduce costs
• Overwriting entire documents unnecessarily

2. Which Firebase syntax correctly updates only specific fields without overwriting the entire document?

easy

A. db.collection('users').doc('abc').set({age: 30}, {merge: true})

B. db.collection('users').doc('abc').set({age: 30})

C. db.collection('users').doc('abc').update({age: 30}, {merge: true})

D. db.collection('users').doc('abc').set({age: 30}, {overwrite: false})

Solution

1. Step 1: Identify update methods in Firebase

   Using set() with {merge: true} updates only specified fields without overwriting the whole document.

2. Step 2: Check options for correctness

   db.collection('users').doc('abc').set({age: 30}, {merge: true}) uses set() with merge: true, which is the correct syntax for partial updates.

3. Final Answer:

   db.collection('users').doc('abc').set({age: 30}, {merge: true}) -> Option A

4. Quick Check:

   Partial update = set with merge true [OK]

Hint: Use set with {merge: true} to update fields only [OK]

Common Mistakes:

• Using set without merge overwrites entire document
• Using update() with invalid merge option
• Using invalid option {overwrite: false}

3. What is the effect of this Firebase code snippet on write operations?

const batch = db.batch();
batch.set(db.collection('users').doc('a'), {name: 'Alice'});
batch.set(db.collection('users').doc('b'), {name: 'Bob'});
batch.commit();

medium

A. Two separate write operations are charged

B. One combined write operation is charged

C. No write operations are charged until batch.commit() is called

D. Writes are charged only if documents exist

Solution

1. Step 1: Understand batch writes in Firebase

   Batch writes group multiple writes to execute atomically but each write counts as a separate operation for billing.

2. Step 2: Count write operations in the snippet

   Two set calls inside the batch mean two write operations charged when commit() runs.

3. Final Answer:

   Two separate write operations are charged -> Option A

4. Quick Check:

   Batch writes count each write separately [OK]

Hint: Batch groups writes but charges per write [OK]

Common Mistakes:

• Thinking batch commit charges only once
• Assuming writes are free before commit
• Believing writes charge only if doc exists

4. You want to update a user's email without overwriting other fields, but your code overwrites the entire document. What is the error?

db.collection('users').doc('user1').set({email: '[e-mail]'});

medium

A. Using update() instead of set()

B. Email field name is invalid

C. Document path is incorrect

D. Missing {merge: true} option in set()

Solution

1. Step 1: Identify why entire document is overwritten

   Using set() without {merge: true} replaces the whole document, causing data loss.

2. Step 2: Fix the code to update only one field

   Add {merge: true} to set() to update only the email field without overwriting others.

3. Final Answer:

   Missing {merge: true} option in set() -> Option D

4. Quick Check:

   Partial update needs merge true [OK]

Hint: Add {merge: true} to set() to avoid overwriting [OK]

Common Mistakes:

• Using set() without merge option
• Confusing update() and set() usage
• Assuming field names cause overwrite

5. You want to reduce Firebase costs by minimizing writes when updating user profiles. Which approach is best to update multiple fields efficiently without overwriting existing data?

hard

A. Use multiple separate set() calls without merge option

B. Use a batch write with set() and merge: true for all updates

C. Use update() for each field separately in different calls

D. Overwrite entire document with set() each time

Solution

1. Step 1: Understand cost impact of writes

   Each write operation costs money. Multiple separate writes increase cost and risk overwriting data.

2. Step 2: Choose efficient update method

   Batch writes combine multiple updates into one commit, reducing network overhead. Using set() with {merge: true} updates only needed fields without overwriting.

3. Final Answer:

   Use a batch write with set() and merge: true for all updates -> Option B

4. Quick Check:

   Batch + merge = efficient partial updates [OK]

Hint: Batch writes with merge true save cost and data [OK]

Common Mistakes:

• Overwriting entire documents unnecessarily
• Using many separate update calls
• Ignoring batch writes for multiple updates