Per-Service Data Ownership: Avoiding Database Monoliths

Key takeaways

• Shared databases create tight coupling, undermining microservices.
• Per-service data ownership enhances scalability and autonomy.
• Adopting event sourcing can facilitate data ownership without redundancy.
• Microservices thrive on decentralized data management for agility.

The problem

Startups often struggle with data management in microservices, particularly when opting for a shared database. This shared approach leads to tight coupling between services, making it difficult to scale independently. When one service requires changes to the database schema, it can impact all dependent services, causing delays and increasing the risk of bugs. Founders frequently encounter these issues as their teams grow, leading to slower deployment cycles and higher operational costs due to the need for extensive coordination.

What we found

A non-obvious insight is that per-service data ownership can significantly enhance the agility and scalability of microservices. By allowing each service to manage its own data, teams can innovate independently without being hindered by the changes of other services. This approach not only minimizes dependencies but also aligns with the principles of Domain-Driven Design (DDD), where each microservice encapsulates its domain and data. Implementing patterns such as event sourcing can help maintain consistency while allowing services to evolve independently.

How to implement it

Begin by identifying the bounded contexts within your application using DDD principles. Each bounded context should correspond to a separate microservice with its own database. Next, implement an API gateway that routes requests to the appropriate service while abstracting the underlying data storage. Consider using event sourcing for data changes, which can help in maintaining a history of events and facilitate eventual consistency across services. Additionally, employ a message broker like Kafka or RabbitMQ to handle inter-service communication and data synchronization efficiently.

How this makes life easier

By adopting per-service data ownership, teams experience increased deployment speed and reduced coordination costs. Services can evolve independently, leading to faster feature releases and improved responsiveness to market changes. This architectural shift can result in a 30-50% reduction in deployment times, as teams are no longer waiting on database schema changes. Furthermore, the risk of cascading failures decreases, enhancing overall system reliability.

Trade-offs of Per-Service Data Ownership

While per-service data ownership offers numerous benefits, it also introduces complexity in data management and eventual consistency. Teams must invest in robust monitoring and logging to ensure data integrity across services. Additionally, the initial setup may require more upfront effort to design appropriate APIs and data models. Balancing these trade-offs is crucial, particularly for startups with limited resources.

30-50% — reduction in deployment times with per-service ownership

40-70% — decrease in inter-service dependencies

20-40% — increase in system reliability after implementing event sourcing

2-3 — average number of services that can be independently deployed per sprint

The solution

To effectively implement microservices, prioritize per-service data ownership by creating distinct databases for each service, leveraging event sourcing, and utilizing a message broker for inter-service communication. This approach will enhance your system's scalability, reliability, and agility.

FAQ

What if my team is small and we can't manage multiple databases?

Start small by applying per-service ownership to your most critical services. As your team grows, gradually refactor other services to follow this model, ensuring you maintain a balance between complexity and manageability.

How do we handle data consistency across services?

Implement eventual consistency using event sourcing and a message broker. This allows services to react to changes asynchronously while maintaining a reliable data flow across the system.

Is it worth the effort to switch from a shared database?

Yes, while the transition requires effort, the long-term benefits in deployment speed and system reliability often outweigh the initial investment.

What tools can help with implementing per-service data ownership?

Consider using tools like PostgreSQL for individual databases, Kafka for event streaming, and Swagger for API documentation to streamline the implementation process.

Originally published at yogreet.com. Yogreet Global is an infrastructure-first product engineering studio — AI cost engineering, microservices and scale roadmapping for startups.