DEV Community: Akshay Sabu

Optimizing Spring Boot Performance: A Practical Guide for Developers

Akshay Sabu — Thu, 02 Apr 2026 04:53:41 +0000

Performance is a critical factor in building scalable and reliable backend systems. While Spring Boot makes development fast and convenient, it’s easy to overlook performance tuning until your application starts slowing down under load.

In this blog, we’ll explore practical strategies to optimize Spring Boot applications for better speed, scalability, and resource efficiency.

⚡ Why Performance Optimization Matters

A slow application can lead to:

Poor user experience 😞
Increased infrastructure costs 💸
Reduced scalability 📉

Optimizing performance ensures your app can handle more users with fewer resources.

🧠 1. Use Spring Boot Starters Wisely

Spring Boot starters bring in many dependencies automatically—but sometimes more than you need.

✅ Best Practice:
Avoid unnecessary starters
Use only required dependencies

<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency>

👉 Tip: Analyze dependencies using mvn dependency:tree

🗄️ 2. Optimize Database Access

Database calls are often the biggest bottleneck.

🔹 Use Connection Pooling

Spring Boot uses HikariCP by default.

spring.datasource.hikari.maximum-pool-size=20 spring.datasource.hikari.minimum-idle=5

🔹 Avoid N+1 Queries

Use JOIN FETCH or @EntityGraph to optimize queries.

🔹 Use Pagination

Never fetch large datasets at once.

Page<User> users = userRepository.findAll(PageRequest.of(0, 10));
🚀 3. Enable Caching

Caching reduces repeated computation and database hits.

🔹 Use Spring Cache
@Cacheable("users") public User getUserById(Long id) { return userRepository.findById(id).orElse(null); }
🔹 Use Redis for Distributed Caching
spring.cache.type=redis
🧵 4. Use Asynchronous Processing

Avoid blocking operations using async methods.

@Async public CompletableFuture<String> processTask() { return CompletableFuture.completedFuture("Done"); }
Enable Async:
@EnableAsync
📦5. Optimize Serialization

JSON serialization can slow down APIs.

🔹 Use Faster Libraries
Jackson (default) is good, but optimize configs
spring.jackson.serialization.FAIL_ON_EMPTY_BEANS=false
🔹 Avoid Returning Large Objects

Use DTOs instead of entities.

🔍 6. Reduce Logging Overhead

Excessive logging impacts performance.

logging.level.root=WARN
✅ Best Practice:
Use DEBUG only in development
Avoid logging inside loops

🧰 7. Use Proper JVM Tuning

JVM settings can significantly impact performance.

-Xms512m -Xmx1024m -XX:+UseG1GC
🔹 Monitor with tools:
JVisualVM
Java Flight Recorder

🌐 8. Enable HTTP Compression

Reduce response size to improve network performance.

server.compression.enabled=true server.compression.mime-types=application/json,application/xml,text/html,text/plain

🔄 9. Use Lazy Initialization

Reduce startup time by loading beans only when needed.

spring.main.lazy-initialization=true

📊 10. Monitor and Profile Your Application

You can’t optimize what you don’t measure.

🔹 Use Spring Boot Actuator
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-actuator</artifactId> </dependency>
🔹 Useful endpoints:
/actuator/health /actuator/metrics /actuator/httptrace

🧪 Bonus Tips

Use WebFlux for reactive applications
Use CDN for static content
Implement rate limiting
Optimize thread pools

🏁 Conclusion

Optimizing Spring Boot performance isn’t about one magic trick—it’s a combination of small improvements across different layers:

Efficient database usage
Smart caching
Proper configuration
Continuous monitoring

Start with the biggest bottlenecks and iterate gradually.

💬 Final Thoughts

Performance tuning is an ongoing process. As your application grows, keep testing, monitoring, and improving.

If you found this helpful, feel free to share or drop your thoughts in the comments.

Storing JSON in PostgreSQL: A Guide to Modern Data Management (With Example in spring boot)

Akshay Sabu — Tue, 13 Aug 2024 06:25:43 +0000

Introduction

In recent years, the acceptance of JSON (JavaScript Object Notation) as a data format has increased due to its flexibility and ease of use to represent structured data PostgreSQL, which is a powerful open-source relational database management system, to store, query and manipulate JSON data directly on your desktop If you embrace this trend by providing strong support this blog explores the benefits, concepts, and best practices of JSON stored in PostgreSQL.

1. JSON in PostgreSQL

PostgreSQL has added support for native JSON with the json andjsonb data types. These types, they enable a developer to store JSON data directly in database columns and this gives you the ability to integrate structured as well as semi-structured data.

There are two main JSON-related data types provided by PostgreSQL: JSON and JSONB.

JSON: Storing JSON data in its original text format, maintains the spacing and order of object keys.
JSONB: manages JSON data and binary format for faster data retrieval than the regular text based storage. It also provides support for indexing to make your queries faster.

2. Advantages of storing JSON in PostgreSQL

Update: JSON data types in PostgreSQL allow storing complex, nested, or dynamic data structures without the need for a predefined schema. This flexibility is ideal for applications with ongoing data requirements.

Query and index: JSONB supports indexing, making it possible to query JSON data even in large data sets. This allows faster data recovery compared to traditional backups.
Schema enhancements: Because JSON structures can evolve without database schema changes, PostgreSQL JSON support simplifies the management of changes to application data models
Application Integration: Many modern web and mobile applications use JSON as the primary data exchange format. Storing JSON directly in PostgreSQL facilitates seamless communication between application data and database storage.

3.Consideration and Best Practices

Data Integrity: While JSON flexibility is beneficial, it can pose a data integrity challenge if not maintained properly. Applications must validate the JSON data before storing it in the database.
Performance: Although JSONB provides efficient indexing and storage, complex JSON structure or frequent updates can affect performance. Proper indexing and query optimization are essential.
Complex query: Writing complex queries against JSON data can be difficult compared to traditional SQL. Understanding PostgreSQL’s JSON functionality and user logic is essential for efficient queries.
Version Compatibility: Ensure that your version of PostgreSQL supports the JSON and JSONB data types and attributes required by your application.

conclusion

The acceptance of JSON in PostgreSQL opens up new ways to manage dynamic data sets in modern applications. While it offers flexibility and efficiency, developers must balance its benefits with considerations such as query complexity and better performance. With proper planning and leveraging PostgreSQL’s JSON capabilities, organizations can leverage the full potential of JSON data storage in their database environment.

Example 1

By Using @JdbcTypeCode(SqlTypes.JSON)

package com.test;

import com.fasterxml.jackson.annotation.JsonIgnore;
import com.fasterxml.jackson.databind.JsonNode;
import jakarta.persistence.*;
import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;
import org.hibernate.annotations.JdbcTypeCode;
import org.hibernate.type.SqlTypes;

@Entity
@Data
@Table(name = "test_class")
@Builder
@NoArgsConstructor
@AllArgsConstructor
public class TestClass {
    @Id
    @GeneratedValue(strategy = GenerationType.SEQUENCE)
    private Long id;

    @JdbcTypeCode(SqlTypes.JSON)
    private JsonNode jsonData;
}

Example 2

-By Using Query

@Autowire
JdbcTemplate jdbcTemplate;

private void addData(long id, JsonNode jsonData){
        String query ="INSERT INTO your_schema.your_table (id, jsonData) VALUES (?, CAST(? AS jsonb))";
        jdbcTemplate.update(query, id, jsonData);
    }