Database normalization vs denormalization in HLD - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding the main goal of normalization

What is the primary purpose of database normalization in system design?

A To combine all data into a single table for simplicity

B To increase the number of tables for faster queries

C To duplicate data across tables for backup

D To reduce data redundancy and improve data integrity

💡 Hint

Think about how normalization helps keep data consistent and organized.

Normalization organizes data to minimize duplication and ensure consistency.

❓ Architecture

intermediate

Choosing denormalization for read-heavy systems

In which scenario is denormalization most beneficial for a database design?

A When the system requires fast read queries with fewer joins

B When data consistency is the highest priority

C When the database size must be minimized

D When the system has very few users and low traffic

💡 Hint

Denormalization duplicates data to speed up reads.

Denormalization improves read performance by reducing the need for complex joins.

❓ scaling

advanced

Impact of normalization on write scalability

How does strict normalization affect the scalability of write operations in a high-traffic database?

A It can slow down writes due to multiple table updates and constraints

B It speeds up writes by reducing the number of tables involved

C It eliminates the need for transactions during writes

D It has no effect on write performance

💡 Hint

Consider how many tables and constraints a write must touch in normalized design.

Normalization requires updating multiple tables and enforcing constraints, which can slow writes.

❓ tradeoff

advanced

Tradeoffs between normalization and denormalization

Which of the following best describes a key tradeoff when choosing between normalization and denormalization?

A Normalization always improves performance; denormalization always reduces storage

B Normalization improves data integrity but may reduce read performance; denormalization improves read speed but risks data inconsistency

C Denormalization eliminates the need for backups; normalization requires frequent backups

D Normalization and denormalization have no impact on system complexity

💡 Hint

Think about the balance between data accuracy and query speed.

Normalization ensures data accuracy but can slow reads; denormalization speeds reads but risks inconsistency.

❓ estimation

expert

Estimating storage impact of denormalization

A normalized database stores 100GB of data. If denormalization duplicates 30% of the data across tables to speed up reads, approximately how much storage will the denormalized database require?

A 70GB

B 100GB

C 130GB

D 230GB

💡 Hint

Calculate original size plus 30% extra for duplicated data.

Denormalization adds 30% more data, so total storage is 100GB + 30GB = 130GB.