---
title: Multi-Database Replication for Microservices
description: Consolidate multiple microservice databases into a single ParadeDB instance for app-wide search and cross-database joins
canonical: https://docs.paradedb.com/deploy/logical-replication/multi-database
---

## Problem Statement

Organizations often have multiple Postgres databases, each connected to a different microservice. The goal is to logically replicate all of these databases into a single ParadeDB instance. This enables:

- App-wide search across all microservices
- Cross-database joins for analytics and reporting
- Centralized data access without modifying individual microservices

However, table naming collisions can occur since each microservice and its database operate independently.

## Logical Replication Background

Postgres' Logical Replication is designed from the perspective of one source database and one destination database. Logical replication resolves tables by their schema-qualified name. It does not have native primitives to remap schema or table names during replication.

## Solution

For logical replication to work, all source database tables need to have a unique signature that avoids name collisions. They also need to be identifiable by their source database. This can be achieved by using a different schema in each database instead of the `public` schema. The schema name should match the database name.

### Architecture

The solution involves replicating multiple independent microservice databases into a single ParadeDB instance. Each source database uses a schema named after the database itself, ensuring no naming conflicts.

![Multi-database replication architecture](/images/multi-database-replication.png)

As shown in the diagram:

- Each microservice database (db1, db2, db3) uses a schema matching its database name
- All databases replicate to a single ParadeDB instance via logical replication
- In ParadeDB, tables are accessible with fully-qualified names (e.g., `db1.table1`, `db2.table1`)
- This enables cross-database joins like: `SELECT db1.users.id, db2.orders.id FROM db1.users JOIN db2.orders ON db1.users.id = db2.orders.user_id`

Instead of having all tables in the `public` schema across multiple databases:

```
Database: users_service
Schema: public
  - users
  - profiles

Database: orders_service
Schema: public
  - orders
  - payments
```

Reorganize each database to use a dedicated schema:

```
Database: users_service
Schema: users_service
  - users
  - profiles

Database: orders_service
Schema: orders_service
  - orders
  - payments
```

This approach ensures that when replicated to ParadeDB, all tables have unique fully-qualified names and you can identify the source of each table.

## Zero-Downtime Migration

This migration strategy reorganizes tables from the `public` schema into dedicated schemas while maintaining complete backwards compatibility through updatable views.

### Migration Steps

For each microservice database, execute the following:

```sql
BEGIN;

-- Create new schema named after the database
CREATE SCHEMA IF NOT EXISTS <database_name>;

-- Move tables to new schema
ALTER TABLE public.table1 SET SCHEMA <database_name>;
ALTER TABLE public.table2 SET SCHEMA <database_name>;
-- Repeat for all tables...

-- Create backwards-compatible views in public schema
CREATE OR REPLACE VIEW public.table1 AS SELECT * FROM <database_name>.table1;
CREATE OR REPLACE VIEW public.table2 AS SELECT * FROM <database_name>.table2;
-- Repeat for all tables...

COMMIT;
```

### Example

For a `users_service` database:

```sql
BEGIN;

-- Create new schema
CREATE SCHEMA IF NOT EXISTS users_service;

-- Move tables
ALTER TABLE public.users SET SCHEMA users_service;
ALTER TABLE public.profiles SET SCHEMA users_service;

-- Create backwards-compatible views
CREATE OR REPLACE VIEW public.users AS SELECT * FROM users_service.users;
CREATE OR REPLACE VIEW public.profiles AS SELECT * FROM users_service.profiles;

COMMIT;
```

### Benefits of This Approach

- **Zero Downtime**: Existing applications continue to function without modification during the transition period for all queries (SELECT, INSERT, UPDATE, DELETE)
- **Gradual Migration**: Application queries can be updated over time to reference the new schema directly
- **Rollback Capability**: Each migration step is reversible if needed
- **View Cleanup**: Once applications are updated, views in the `public` schema can be safely removed

### Setting Up Logical Replication

After completing the schema migration for all source databases:

1. Configure each source database as a publisher following the [getting started guide](/deploy/logical-replication/getting-started)
2. Set up ParadeDB as a subscriber for all source databases
3. Create publications on each source database for their respective schemas:

```sql
-- On users_service database
CREATE PUBLICATION users_pub FOR TABLES IN SCHEMA users_service;

-- On orders_service database
CREATE PUBLICATION orders_pub FOR TABLES IN SCHEMA orders_service;
```

4. Create subscriptions on ParadeDB for each source database:

```sql
-- On ParadeDB instance
CREATE SUBSCRIPTION users_sub
    CONNECTION 'host=users_db port=5432 dbname=users_service user=replicator password=...'
    PUBLICATION users_pub;

CREATE SUBSCRIPTION orders_sub
    CONNECTION 'host=orders_db port=5432 dbname=orders_service user=replicator password=...'
    PUBLICATION orders_pub;
```

## Trade-offs

### Pros

- **Multi Database BM25 Search**: Perform full-text search across tables distributed across multiple microservice databases in a single query
- **Avoid Distributed Joins in Application**: Execute cross-database joins directly in ParadeDB instead of implementing complex join logic in your application
- **Simple Architecture**: Uses standard PostgreSQL logical replication without extra infrastructure
- **Namespace Isolation**: Schema-based separation prevents naming conflicts
- **No Source Database Changes**: Microservices continue operating independently; ParadeDB acts as a read replica

### Cons

- Source databases will access tables from their dedicated schema (e.g., `users_service`) instead of `public`
- Requires coordination across microservice teams for initial migration
- Existing database tooling may need configuration updates to work with non-public schemas
