Microservice Database Best Practice

Should Multiple Microservices Connect to One Database?

The short answer: Each microservice should have its own database rather than sharing a single database.

This is known as the Database per Service pattern in microservices architecture.

However, there are trade-offs, and the decision depends on factors like performance, data consistency, and maintainability.

Best Practice: Each Microservice Has Its Own Database

Each microservice should have exclusive control over its own database. This ensures loose coupling, better scalability, and independent deployment.

Benefits of Database per Microservice

Loose Coupling & Independence

Services remain fully autonomous and can evolve independently.

There is no risk of one service accidentally modifying another service’s data.

Scalability & Performance

Each microservice can use a database technology optimized for its needs (e.g., SQL, NoSQL, Graph DB).

Services can be scaled individually based on workload.

Improved Fault Isolation

If one service crashes or a database experiences high load, other services remain unaffected.

Independent Deployment & Schema Evolution

No database schema dependencies between services which allows microservices to evolve without breaking other services.

Security & Data Ownership

Sensitive data is accessible only to the owning service, reducing unauthorised access risks.

This provides easier compliance with GDPR and other security policies.

While sharing a database across multiple microservices might seem convenient, it leads to strong coupling, limiting the benefits of microservices.

Problems with a Shared Database:

Tightly Coupled Architecture

Services become dependent on the same schema, making independent deployments harder.

Schema changes in one service can break another service.

Scalability Bottlenecks

A single database can become a performance bottleneck as traffic increases.

Services cannot scale independently if they all rely on the same database.

Data Ownership Issues

Who is responsible for making schema changes if multiple teams own the same database?

The coordination overhead increases.

Difficult to Enforce Data Consistency

Transactions spanning multiple services require distributed transactions (2PC), which reduce performance and increase complexity.

Security Risks

A security vulnerability in one microservice can expose the entire database to unauthorised access.

If microservices need to share data, they should do so through API calls or an event-driven approach, rather than directly accessing a shared database.

Recommended Alternatives

Approach	How It Works	Best For
API Communication	Microservices expose REST/gRPC APIs to share data.	When real-time data is required.
Event-Driven Architecture (Kafka, RabbitMQ)	Services publish and consume events without direct database access.	Loose coupling and asynchronous processing.
Change Data Capture (CDC)	Services listen for database changes (Debezium, Kafka CDC).	Data replication without direct access.
Data Replication	Services replicate data to their own database.	Read-heavy services needing fast access to shared data.

In some rare cases, microservices may share a database with strict boundaries:

Acceptable Scenarios for a Shared Database

Legacy System Migration
- If you're breaking a monolith into microservices incrementally, it may be practical to use a shared database temporarily.
Low-Scale Applications
- For a small application, managing multiple databases may be unnecessary overhead.
Read-Only Reporting Database
- A shared read-only replica for analytics, reporting, or BI tools can be acceptable.

Key Rule: If microservices must share a database, they should never directly modify another service’s tables. Instead, each service should only access its own schema.

Conclusion: Best Approach?

Each microservice should have its own database (Database per Service).
Services should communicate via APIs, events, or data replication instead of directly accessing shared tables.
A shared database should only be used as a temporary or read-only solution.

By following these principles, you ensure scalability, independence, and maintainability in your microservices architecture.