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Data Management in Microservices: Best Practices for Consistency and Scalability
How, When, Why, and Tech Stack for Effective Data Management
In the complex world of microservices, managing data can be tricky. With multiple services interacting, keeping data consistent and reliable can be tough. But don’t worry, developers! Here are 8 approaches to help you handle data challenges and keep your microservices running smoothly
1. Database per Service: The Independence Champion
When:- Services require high independence and loose coupling.
Why: Ensures each service can evolve independently without affecting others, minimizing cross-service failures.
How: Each microservice has its own private database, using different schemas or even different database systems.
Tech Stack: MySQL, PostgreSQL, MongoDB, Cassandra.
2. Shared Database: The Data Sharing Pro
When: Services need to share data frequently and consistency is critical.
Why: Simplifies data access and reduces latency by avoiding data duplication.
How: All services access the same database, often with well-defined schemas and access controls.
Tech Stack: MySQL, PostgreSQL, Oracle, SQL Server.
