A Comprehensive Guide to Optimizing Queries in Spring Boot for Small, Medium, and Large Data Sets

Efficient query handling is the cornerstone of building performant applications, especially as data scales from small sets to massive, complex datasets. As a Spring Boot developer, optimizing your database queries for different data sizes — small, medium, and large — can significantly improve your application’s performance. This guide dives deep into the best practices, modern techniques, and tools to optimize queries, enhance performance, and ensure scalability in your Spring Boot applications.

Optimizing Queries for Small Data (Hundreds to Thousands of Rows)

For small datasets, the focus should be on simplicity and minimizing overhead. Though performance issues are not as prominent here, building with scalability in mind ensures that your application can handle future growth.

Key Techniques:

• Eager Fetching: Small datasets can benefit from eager fetching, where related entities are loaded in the same query, reducing the number of database calls. This is ideal when working with a limited number of records that have relationships.

@ManyToOne(fetch = FetchType.EAGER)
private Category category;