Data denormalization strategies in Firebase - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is data denormalization in Firebase?

Data denormalization in Firebase means storing data in multiple places to make reading faster and simpler, even if it means some data is repeated.

beginner

Why do we denormalize data in Firebase instead of normalizing it like in SQL databases?

Firebase is a NoSQL database optimized for fast reads and simple queries. Denormalizing avoids complex joins and multiple reads, improving performance and user experience.

beginner

Name one common strategy for data denormalization in Firebase.

One common strategy is duplicating related data in multiple places, such as copying user profile info inside each post they create, so the app reads all needed data in one go.

intermediate

What is a potential downside of data denormalization?

The main downside is data inconsistency risk because the same data exists in multiple places and must be updated everywhere when changed.

intermediate

How can you keep denormalized data consistent in Firebase?

You can use Firebase transactions or Cloud Functions to update all copies of the data atomically or automatically when one copy changes.

Why is data denormalization used in Firebase?

A To prevent any data duplication

B To reduce storage space by removing duplicates

C To enforce strict data relationships like SQL

D To speed up data reads by duplicating data

Denormalization duplicates data to make reads faster and simpler in Firebase.

What is a risk when denormalizing data?

A Less storage used

B Slower data reads

C Data inconsistency if updates are not synced

D Automatic data validation

Duplicated data can become inconsistent if all copies are not updated properly.

Which Firebase feature helps keep denormalized data consistent?

A Cloud Functions

B Realtime Database rules only

C Static hosting

D Firebase Analytics

Cloud Functions can automate updates to all copies of denormalized data.

In Firebase, denormalization means:

A Storing related data together in multiple places

B Splitting data into many small tables

C Using SQL joins for queries

D Removing all duplicate data

Denormalization stores related data together in multiple places to simplify reads.

Which is NOT a benefit of denormalization in Firebase?

A Faster data retrieval

B Automatic data consistency

C Simpler queries

D Reduced need for complex joins

Denormalization requires extra work to keep data consistent; it is not automatic.

Explain what data denormalization is and why it is used in Firebase.

Think about how Firebase handles data differently than SQL databases.

Describe strategies to keep denormalized data consistent in Firebase.

Consider how to update multiple copies of the same data safely.