Why Multi-Tenancy Is Hard
Multi-tenancy sounds simple: multiple customers sharing the same application. In practice, it's a minefield of:
- →Data isolation concerns
- →Performance interference (noisy neighbors)
- →Customization requirements
- →Compliance and security demands
Pattern 1: Database-Per-Tenant (When It Makes Sense)
Despite higher operational overhead, database-per-tenant offers:
- →Complete data isolation
- →Simple compliance (data residency)
- →Easier backup and restore per customer
Best for: Healthcare, finance, enterprise clients with strict requirements.
Pattern 2: Schema-Per-Tenant (The Middle Ground)
Shared database, separate schemas. You get:
- →Reasonable isolation
- →Easier cross-tenant analytics
- →Lower operational costs than database-per-tenant
Best for: B2B SaaS with moderate data sensitivity.
Pattern 3: Row-Level Isolation (Maximum Efficiency)
All tenants share tables, isolated by tenant_id. Requires:
- →Rock-solid RLS policies
- →Careful query optimization
- →Robust testing for data leakage
Best for: High-volume, cost-sensitive applications.
Choosing the Right Pattern
There's no universal answer. I typically recommend:
- →Start with row-level isolation for speed
- →Prepare migration paths for larger tenants
- →Offer database isolation as a premium tier