Database decomposition strategy in Microservices - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is database decomposition in microservices?

Database decomposition means splitting a big database into smaller, independent databases for each microservice. This helps services work independently and scale better.

beginner

Name two common strategies for database decomposition.

1. Vertical decomposition: splitting by business capabilities or domains.<br>2. Horizontal decomposition: splitting by rows or data ranges.

intermediate

Why is it important for each microservice to have its own database?

Having separate databases avoids tight coupling, allows independent scaling, and reduces the risk of one service affecting others.

intermediate

What challenges arise from database decomposition in microservices?

Challenges include data consistency across services, complex queries needing data from multiple databases, and managing distributed transactions.

advanced

How can eventual consistency help in database decomposition?

Eventual consistency allows services to update their own databases independently and sync changes asynchronously, improving performance and availability.

What is the main goal of database decomposition in microservices?

A To split a large database into smaller, service-specific databases

B To merge multiple databases into one big database

C To create backups of the database

D To encrypt the database for security

Database decomposition splits a large database into smaller ones owned by individual microservices.

Which decomposition strategy splits data by business capabilities?

A Horizontal decomposition

B Functional decomposition

C Data replication

D Vertical decomposition

Vertical decomposition splits the database by business domains or capabilities.

What is a common challenge when using separate databases per microservice?

A Faster queries

B Data consistency across services

C Simpler backups

D Reduced network traffic

Maintaining data consistency across multiple databases is a key challenge.

Which approach helps microservices sync data asynchronously?

A Strong consistency

B Synchronous replication

C Eventual consistency

D Monolithic database

Eventual consistency allows asynchronous syncing between services.

Why should microservices avoid sharing a single database?

A It increases coupling and reduces scalability

B It improves data security

C It simplifies deployment

D It reduces data duplication

Sharing a database creates tight coupling and limits independent scaling.

Explain the main strategies for decomposing a database in a microservices architecture and their benefits.

Think about splitting data by function or by data slices.

Describe the challenges that arise from database decomposition and how eventual consistency can address some of them.

Consider what happens when data is spread across services.