Good Practices for Data Modeling in a Domain Data Store for Microservices
So, you’ve jumped on the microservices train—congrats! Your app is now a beautiful mess of independent services, each doing its own thing, living its best life. But wait… your data model is an absolute disaster.
Tables are tangled like last year’s Christmas lights. Queries take longer than your coffee break. And your team? They’re crying.
1. One Service, One Database
First rule of microservices club: each service gets its own database. No sharing. No “but it’s just one little table.” No “let’s just put everything in PostgreSQL and hope for the best.”
Every service should own its data and expose it through well-defined APIs. If you need data from another service, call its API like a civilized developer, don’t go sneaking into its database like a hacker in the night.
2. Pick the Right Database for the Job
Not every database is an all-you-can-eat buffet. Some are good for transactions (SQL), some are good for unstructured data (NoSQL), and some exist just to make your life miserable (looking at you, legacy Oracle setups).
General Guidelines:
- SQL (PostgreSQL, MySQL, etc.) → If you need ACID transactions and strong consistency.
- NoSQL (MongoDB, DynamoDB, etc.) → If you’re dealing with large-scale, flexible schemas.
- Event Stores (Kafka, EventStoreDB, etc.) → If your system is all about event-driven magic.
Choose wisely. Your future self will thank you.
3. Design for Loose Coupling, Not Data Entanglement
If your microservices have to talk directly to each other’s databases, you have a distributed monolith, not microservices. That’s a one-way ticket to maintenance hell.
Instead:
- Use API calls or events to communicate.
- Embrace eventual consistency where possible.
- Use an event-driven architecture for things that don’t need immediate synchronization.
Trust me, letting go of synchronous dependencies is like removing a toxic relationship from your life—suddenly, everything feels lighter.
4. Schema Versioning: Because Change is Inevitable
Your schema will change. And if you’re not ready for it, your microservices will crash harder than my last New Year’s resolution.
- Use database migrations (Flyway, Liquibase, or custom scripts) to evolve schemas smoothly.
- Apply backward compatibility—new changes should not break old services.
- Consider blue-green deployments for database changes that require downtime.
5. CQRS & Event Sourcing: Fancy but Useful
CQRS (Command Query Responsibility Segregation) and Event Sourcing can seem like unnecessary wizardry, but in some cases, they make life easier.
- CQRS → Separate read and write models for better scalability.
- Event Sourcing → Store every change as an event instead of just updating rows.
Use these only if your system benefits from them. Otherwise, you might just be adding complexity for fun.
6. Data Replication & Caching: Speed is Life
Nothing kills a microservices system faster than slow queries.
- Use caching (Redis, Memcached, etc.) to store frequently accessed data.
- Replicate databases if you need high availability and performance.
- Consider read replicas if your read-heavy services need a boost.
7. Data Privacy & Security: Don’t Get Hacked
- Encrypt sensitive data at rest and in transit.
- Use IAM roles and least-privilege access for databases.
- Audit logs are your friend when debugging security incidents.
- Validate all inputs—SQL injection is still a thing.
8. Backups: Because Things Will Go Wrong
Nothing makes you appreciate backups more than the moment you realize you don’t have one.
- Automate daily backups.
- Test your restore process (because an untested backup is as good as no backup).
- Keep multiple copies (local + cloud, if possible).
Conclusion
Building a data model for microservices is part art, part science, and part “oh no, what have I done?” But if you follow these best practices, your system will be scalable, maintainable, and (hopefully) not a source of daily frustration.
Remember:
- Each service gets its own database.
- Pick the right DB for the job.
- Loose coupling = happy developers.
- Expect schema changes and plan for them.
- Performance and security are not optional.
Now go forth and build something that doesn’t make your future self cry. 🚀
Key Ideas
| Concept | Summary |
|---|---|
| One Service, One DB | Each microservice should own its own database. No sharing. |
| Right Database Choice | Use SQL, NoSQL, or Event Stores based on your needs. |
| Loose Coupling | Avoid direct database access; use APIs or events. |
| Schema Versioning | Plan for migrations and backward compatibility. |
| CQRS & Event Sourcing | Useful for scalability but only if necessary. |
| Caching & Replication | Speed up queries with caching and replicas. |
| Security & Privacy | Encrypt, use IAM roles, and validate inputs. |
| Backups | Automate and test backups to avoid disasters. |