Quarkus vs Spring: Performance, Developer Experience, and Production Trade-offs : Part 1

Source: Dev.to

Background

Since the advent of Spring Boot, it has been the de‑facto backend framework for Java web developers, thanks to its developer‑friendly ecosystem, autoconfiguration magic, and ready‑to‑code setup (Spring starters).

In the age of cloud, several other frameworks have emerged, such as Micronaut and Quarkus. This article focuses on Quarkus, how it differs from Spring Boot, why cloud adoption has prompted companies to rethink framework choices, and what Spring’s answer to Quarkus is.

Spring Boot Internals

Spring uses reflection heavily for autoconfiguration, providing an excellent developer experience. Stereotypes, component scanning, configuration files declaring beans for classes outside the container using @Bean, Spring Data JPA interfaces, and more are autoconfigured via reflection. Spring creates proxies at runtime to set up the Spring container, which results in high RAM usage and slower application startup.

To illustrate, consider a typical BeanCreationException you might encounter while working with Spring (see the official Javadoc). This exception occurs when Spring tries to create the application context at startup, resolving all dependencies and instantiating beans in their respective scopes. It demonstrates that Spring beans are created at runtime during application‑context initialization.

Impact on Cloud Deployments

Organizations are moving to microservices architectures for reliability and scalability. Systems are being deployed to cloud environments to reduce costs compared to on‑premises infrastructure, leveraging a plethora of out‑of‑the‑box options for various use cases.

A monolith is split into multiple microservices based on domain‑driven design principles. Each microservice typically runs several replica instances, each with its own compute and memory resources. Imagine a system where hundreds—or even thousands—of microservices run in the cloud; each pod consumes memory and compute resources, driving up the cloud bill.

Now consider an alternative that is roughly 10× faster on average and uses 1/10th of the memory. The cost savings are substantial, though the trade‑off may be developer experience. This is the promise Quarkus brings to the table.

Looking Ahead

We have briefly examined how Spring works internally and the challenges it faces when integrating with cloud environments. In the next part, we will explore how Quarkus addresses these cloud challenges and what the Spring team is doing to mitigate them.