Denormalization tradeoffs in DBMS Theory - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is denormalization in database design?

Denormalization is the process of intentionally adding redundant data to a database to improve read performance by reducing the number of joins needed.

beginner

Name one main advantage of denormalization.

It improves query speed by reducing the need to join multiple tables, making data retrieval faster.

beginner

What is a key disadvantage of denormalization?

It can cause data inconsistency because redundant data must be updated in multiple places, increasing maintenance complexity.

beginner

How does denormalization affect storage space?

Denormalization increases storage space usage because it stores duplicate data across tables.

intermediate

When might denormalization be a good choice?

When read performance is critical and the database workload involves many complex queries, denormalization can speed up data access despite extra storage and maintenance.

What is the primary goal of denormalization?

A Improve read query performance

B Reduce data redundancy

C Simplify database schema

D Eliminate data duplication

Denormalization aims to improve read query speed by adding redundant data, not reducing it.

Which is a common risk when using denormalization?

A Data inconsistency

B Faster writes

C Reduced storage needs

D Simpler updates

Denormalization can cause data inconsistency because the same data is stored in multiple places.

Denormalization usually leads to:

A Less storage space used

B Faster data retrieval

C More joins in queries

D Elimination of redundant data

Denormalization reduces joins and speeds up data retrieval but increases storage.

Which scenario favors denormalization?

A Heavy write operations with few reads

B Simple data with no redundancy

C Complex queries needing fast reads

D Small databases with few users

Denormalization helps when complex queries require fast read access.

What must be carefully managed in a denormalized database?

A Eliminating tables

B Reducing query speed

C Removing indexes

D Data duplication updates

Updates must be carefully managed to keep duplicated data consistent.

Explain the tradeoffs involved in denormalization of a database.

Think about what you gain and what you lose when adding redundant data.

When would you choose denormalization over normalization in database design?

Consider the balance between performance needs and data integrity.