1. What is Database per Service in Microservices?

In a traditional monolithic application, all parts of the system share a single database. In contrast, microservices break the application into smaller, independent services, each managing a specific part of the business logic. The Database per Service pattern ensures that each of these services has its own independent database, which means no other service can directly access its data.

1.1 Decoupling Services

Each microservice operates independently, without depending on a shared database schema. This decoupling ensures that changes to the database of one service don’t affect the others. For instance, if you update the database schema of one service, you won’t need to worry about inadvertently breaking another service’s functionality.

1.2 Improved Scalability

Since each microservice manages its own database, you can scale the services independently. This is particularly beneficial for services with varying levels of traffic. If one service needs more database resources, you can scale only that service’s database without having to upgrade the entire system.

Example Code: Using PostgreSQL in a Spring Boot Microservice

// Service class using PostgreSQL for a product catalog microservice

@Service
public class ProductService {

    @Autowired
    private ProductRepository productRepository;

    public List<Product> findAllProducts() {
        return productRepository.findAll();
    }

    public Product addProduct(Product product) {
        return productRepository.save(product);
    }
}

The ProductService is independent and accesses its own PostgreSQL database through ProductRepository. This is a clear example of decoupling, where the service owns its data and no other service has direct access.

1.3 Flexibility in Database Choices

Each service can use the most appropriate database technology for its requirements. For example, a service responsible for real-time analytics may use a NoSQL database like MongoDB, while another service handling transactions might use a relational database like MySQL or PostgreSQL.

1.4 Easier Maintenance

When services have independent databases, teams can work on them in isolation. Maintenance tasks such as database schema updates, performance tuning, and backups are easier to manage without the fear of breaking other services.

2. Benefits of Database per Service Strategy

Now that we understand what Database per Service entails, let’s explore its benefits. These advantages make it a compelling choice for microservice architectures, especially for complex systems.

2.1 Enhanced Security

When each service has its own database, you can enforce stricter access control policies. Each microservice only has permission to interact with its own database, limiting the scope of potential security vulnerabilities.

For example, if a service handles sensitive customer data, it can be isolated with additional security measures, such as encryption and access controls, that other services might not need.

Example Code: Spring Security Config for Isolating a Service

@EnableWebSecurity
public class SecurityConfig extends WebSecurityConfigurerAdapter {

    @Override
    protected void configure(HttpSecurity http) throws Exception {
        http
            .authorizeRequests()
            .antMatchers("/customer/**").hasRole("ADMIN")
            .antMatchers("/public/**").permitAll()
            .anyRequest().authenticated()
            .and()
            .formLogin().permitAll();
    }
}

Here, access to the customer service is restricted to only users with the role of ADMIN, adding an extra layer of security.

2.2 Optimized Performance

By segregating databases, you can fine-tune each service's performance independently. Services that handle higher traffic can have their databases optimized specifically for read-heavy or write-heavy workloads. This tuning can be impossible or impractical with a single shared database.

For example, a service dealing with real-time analytics could benefit from using an in-memory database, like Redis, to reduce latency, while a traditional service might stick with relational databases for ACID transactions.

3. Challenges of Database per Service

While this pattern offers many benefits, it’s important to be aware of the challenges involved. Implementing Database per Service is not without trade-offs.

3.1 Increased Complexity

Managing multiple databases adds complexity in terms of deployment, monitoring, and backup strategies. If you have many microservices, each with its own database, maintaining consistency across these databases can be daunting.

3.2 Data Consistency Issues

A major challenge is ensuring data consistency across services, especially in systems where multiple services need to share data. This issue can often be solved by implementing a Saga Pattern or using Eventual Consistency models , but it adds to the complexity.

Example Code: Implementing Saga Pattern with Kafka

@Service
public class OrderService {

    @Autowired
    private KafkaTemplate<String, OrderEvent> kafkaTemplate;

    public void createOrder(Order order) {
        // Save order in the database
        orderRepository.save(order);
        // Publish an event for other services
        kafkaTemplate.send("order-events", new OrderEvent(order));
    }
}

In this example, an OrderService publishes events to Kafka. Other services listen to these events and update their databases accordingly, ensuring eventual consistency across services.

3.3 Cross-Service Queries

With separate databases, querying across services becomes difficult. You can no longer join data across services using SQL queries. Instead, you’ll need to use API calls or event-based architectures to gather data from multiple services.

4. When to Use Database per Service?

While the Database per Service pattern offers many advantages, it may not be suitable for every scenario. It’s essential to evaluate when this strategy is the right fit.

4.1 Large-Scale Systems

If your system consists of many microservices and handles a large volume of data, using independent databases will help you manage complexity and improve performance.

4.2 Domain-Driven Design

If your microservices are built around distinct business domains (e.g., customer, orders, inventory), it makes sense to give each service its own database, following the principles of domain-driven design.

5. Conclusion

Using a Database per Service approach in microservices architecture offers significant advantages in terms of security, performance, scalability, and maintainability. However, it also brings increased complexity and challenges in ensuring data consistency and managing cross-service queries.

In systems with independent business domains or high scalability needs, the Database per Service pattern is an excellent choice. By decoupling services at the database level, you gain the flexibility to choose the best database for each service's needs and scale them independently.

If you have questions or need further clarification on any point, feel free to leave a comment below!

Read posts more at : Reasons Why You Should Use Database per Service in Microservices Architecture