Implementing Caching in Fullstack Java with Spring Cache

In fullstack Java applications, performance is often a top concern—especially when dealing with frequent database queries or time-consuming service calls. A simple and highly effective way to enhance performance is by implementing caching. With Spring Framework’s built-in support for caching via Spring Cache, developers can boost application speed with minimal code changes. In this blog post, we'll explore how to implement caching in a fullstack Java application using Spring Cache.

Why Caching Matters

Imagine your application retrieves data from a database or an external API repeatedly. Each call consumes time and resources. If the data doesn’t change often, it’s inefficient to fetch it every time. That’s where caching helps:

• Reduces latency by serving data from memory.
• Decreases database load and network traffic.
• Improves scalability during high traffic.

Spring Cache Overview

Spring provides a simple abstraction for caching that works with multiple providers like Ehcache, Caffeine, Redis, and more. With just a few annotations, you can configure caching for methods that retrieve expensive or slow data.

Getting Started: Setup

To begin, add the necessary dependency to your pom.xml if using Maven:

xml

<dependency>

  <groupId>org.springframework.boot</groupId>

  <artifactId>spring-boot-starter-cache</artifactId>

</dependency>

Optionally, add a cache provider like Caffeine:

xml

<dependency>

  <groupId>com.github.ben-manes.caffeine</groupId>

  <artifactId>caffeine</artifactId>

</dependency>

Enable caching in your Spring Boot application by adding the @EnableCaching annotation:

java

@SpringBootApplication

@EnableCaching

public class Application {

    public static void main(String[] args) {

        SpringApplication.run(Application.class, args);

    }

}

Caching in Action

Let’s say you have a service that fetches product details:

java

Copy

Edit

@Service

public class ProductService {

    @Cacheable("products")

    public Product getProductById(Long id) {

        simulateSlowService();

        return productRepository.findById(id).orElse(null);

    }

    private void simulateSlowService() {

        try {

            Thread.sleep(3000); // Simulate latency

        } catch (InterruptedException e) {

            throw new IllegalStateException(e);

        }

    }

}

The @Cacheable("products") annotation tells Spring to cache the result of the method. If the method is called again with the same ID, the cached result is returned instantly—bypassing the database and skipping the delay.

Other Useful Cache Annotations

@CachePut – Updates the cache without skipping method execution.

@CacheEvict – Removes data from the cache when changes occur.

Example:

java

@CacheEvict(value = "products", key = "#id")

public void deleteProduct(Long id) {

    productRepository.deleteById(id);

}

This ensures the cache stays in sync when data is deleted.

Customizing Cache Configuration

You can customize the cache provider via application.properties:

properties

spring.cache.type=caffeine

spring.cache.cache-names=products

spring.cache.caffeine.spec=maximumSize=1000,expireAfterWrite=10m

Conclusion

Caching is one of the easiest ways to drastically improve application performance, and Spring Cache makes it nearly effortless. With just a few annotations, you can reduce database load, improve response times, and scale your application more effectively. Whether you’re working on a microservice or a monolith, implementing caching in your fullstack Java app is a best practice you shouldn’t ignore.

For more advanced setups, consider integrating distributed caches like Redis, especially if your application is deployed across multiple instances. But even local caching with Spring Cache can go a long way in boosting performance.

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