Shared Database vs Database Per Service: Data Ownership in Microservices

Sun, 06 Sep 2026 09:52:35 +0900

Overview

This compares two data architecture patterns for microservices: a shared database where multiple services read and write the same schema, versus database per service where each service owns an isolated data store. The choice determines how tightly services are coupled, how transactions and queries span service boundaries, and how independently teams can deploy and scale.

Comparison Diagram

Comparison Table

Aspect	Shared Database	Database Per Service
Schema ownership	One schema shared and often co-owned by multiple teams	Each service exclusively owns and evolves its own schema
Write path	Any service can write directly to shared tables	Writes go only through the owning service’s API
Cross-service queries	Simple SQL joins across tables in one database	Requires API calls, data replication, or an aggregation layer
Distributed transactions	Native ACID transactions across affected tables	Needs sagas or eventual consistency to span services
Schema migrations	Any change risks breaking other services using the table	Migrations are local and safe to run independently
Independent scaling	Database becomes a shared bottleneck under load	Each store can be scaled or tuned to its own service’s needs
Technology choice	All services locked into one database engine	Each service can pick the best-fit database technology
Failure isolation	A database outage or lock contention affects every service	An outage is contained to the owning service’s data

Key Differences

Shared database allows cheap cross-table joins but couples every consuming service to one schema
Database per service enforces service autonomy at the cost of needing sagas for cross-service transactions
Schema changes in a shared database require coordinating multiple teams, while per-service schemas change independently
A shared database creates a single failure domain; per-service databases contain outages to one service
Polyglot persistence — choosing different database engines per need — is only possible with database per service

When to Use Each

Shared Database

Shared Database vs Database per Service: Data Ownership in Microservices

Tue, 04 Aug 2026 05:14:24 +0900

Overview

A shared database lets multiple services read and write the same tables through one common schema, while database per service gives each service its own private data store that only it can touch directly. The choice determines how tightly services are coupled at the data layer, how independently teams can deploy, and how much work cross-service queries and transactions require.

Comparison Diagram

Comparison Table

Aspect	Shared Database	Database per Service
Data ownership	No single owner — all services see and can modify the same tables	Each service exclusively owns its schema; no one else can touch it directly
Access path	Services query the database directly, often with raw SQL against shared tables	Other services only get data through the owning service’s API or published events
Cross-service transactions	Native ACID transactions and joins span all the data in one commit	No shared transaction; consistency across services needs sagas or eventual consistency
Cross-service queries	Simple SQL joins pull data from any table in one query	Requires API composition, data replication, or a separate CQRS read model
Schema changes	A column or table change can silently break unrelated services	Schema changes are internal; only the public API contract must stay stable
Technology choice	All services are locked into one database engine and schema	Each service can pick the storage engine that fits its data (polyglot persistence)
Failure isolation	A database outage or lock contention affects every service at once	An outage in one service’s database doesn’t directly take down the others
Operational overhead	One database to provision, back up, and tune	N databases to provision, monitor, back up, and scale independently

Key Differences

Shared database gives every service direct access to the same tables, so a change in one place can silently break another service’s queries — a form of tight coupling.
Database per service forces all cross-service data access through an API, giving each service true encapsulation of its data.
Cross-entity consistency is a native ACID transaction in a shared database, but needs a saga pattern or eventual consistency once data is split per service.
Reporting and ad-hoc joins are trivial with a shared database’s SQL, while database per service usually needs a separate CQRS read model to answer cross-service queries.
Database per service allows polyglot persistence — each service picks its own database engine — whereas shared database locks every service to one engine and schema.

When to Use Each

Shared Database

System-Architecture on IT Comparison

Shared Database vs Database Per Service: Data Ownership in Microservices

Overview

Comparison Diagram

Comparison Table

Key Differences

When to Use Each

Shared Database vs Database per Service: Data Ownership in Microservices

Overview

Comparison Diagram

Comparison Table

Key Differences

When to Use Each