multi-tenant-data-partitioner

Purpose

Architect secure, cost-effective, and scalable database multi-tenancy models (Shared Database/Shared Schema with Row-Level Security, Database-per-Tenant, Schema-per-Tenant) tailored to compliance, isolation, and cost constraints.

When to Use

• Designing the data architecture for a B2B SaaS application.
• Enterprise customers requesting strict physical data isolation or custom backup schedules.
• Evaluating database costs vs cross-tenant data leakage risks.

What to Analyze

1. Isolation Model Selection:
   • Shared Database, Shared Schema (Pool): Highest resource efficiency, lowest cost, enforced via Postgres RLS.
   • Separate Schema (Bridge): Logical isolation, schema migration overhead at 1,000+ tenants.
   • Separate Database (Silo): Complete physical isolation, highest cost, individual tenant disaster recovery.
2. Tenant Context Resolution: Subdomain (tenant.app.com), JWT claim, or custom HTTP header routing.
3. Connection Pool Management: Dynamic connection routing without exhausting database connection limits.
4. Cross-Tenant Leakage Prevention: Automated query filters and database-enforced Row-Level Security (RLS).
5. Noisy Neighbor Defense: Per-tenant query rate limits and compute quotas.

Output Format

• Multi-Tenancy Tradeoff Matrix: Comparison of Pool vs Bridge vs Silo for your specific scale.
• Postgres Row-Level Security (RLS) Policy: SQL script enforcing tenant_id session boundaries.
• Tenant Routing Middleware: Code extracting and injecting tenant context into database queries.

Avoid

• Relying solely on application-level WHERE tenant_id = :id queries without database-level RLS enforcement.
• Creating 10,000 PostgreSQL schemas on a single instance (causes heavy catalog metadata lock contention).