When decomposing a monolith into microservices and the shared database pattern must be broken.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: Databases & Data Engineering - Use case: Data Modelling for Microservices - Source task: - Design data storage for a microservices architecture with these services: {{list_your_services}}. Apply the Database per Service pattern. For each service: - 1. recommended database type and why - 2. data it owns (never shared directly) - 3. how it exposes data to other services (events, APIs, read models) - 4. how to handle cross-service queries that previously would have been a JOIN - 5. saga pattern design for the most complex cross-service transaction # Goal Per-service database recommendations, data ownership definitions, cross-service data sharing patterns, and a saga design for the hardest transaction. # Constraints - Produce a complete, usable first draft in one response. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Per-service database recommendations, data ownership definitions, cross-service data sharing patterns, and a saga design for the hardest transaction.
{{double-curly}} with your real context.When decomposing a monolith into microservices and the shared database pattern must be broken.
Resist the temptation to share a database between services — it creates coupling that defeats the purpose of microservices entirely.
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