docs: multi tenant database architecture

Author: tianzhou

content/blog/multi-tenant-database-architecture-patterns-explained.md

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+---
+title: Multi-Tenant Database Architecture Patterns Explained
+author: Tianzhou
+updated_at: 2025/03/15 10:00:00
+feature_image: /content/blog/multi-tenant-database-architecture-patterns-explained/banner.webp
+tags: Explanation, Hidden
+featured: true
+description: A deep dive into multi-tenant database architecture patterns, exploring pros and cons of shared vs. isolated models, and how to choose the right approach for your SaaS application.
+---
+
+We frequently hear from prospects about their schema migration challenges. One of the top three pain points is managing schemas where they employ a single DB per tenant architecture.
+
+When building a SaaS application, deciding how to structure your database architecture for multiple tenants is a critical decision that impacts scalability, security, cost, and operational complexity. There are two primary approaches:
+
+- **Single database for all tenants**
+- **One database per tenant**
+
+It's a recurring topic asked like in this [Reddit post](https://www.reddit.com/r/Database/comments/1j7682a/multitenant_database/) and has sparked a lot of tears in [HackerNews](https://news.ycombinator.com/item?id=23305111).
+
+## Multi-Tenant Database Architecture Patterns
+
+Let's explore the common patterns for multi-tenant database architectures:
+
+### Pattern 1: Shared Everything
+
+In this model, all tenants share the same database and the same tables. This is achieved by adding a `tenant_id` column to each table that requires tenant separation.
+
+```sql
+CREATE TABLE customers (
+  id INT PRIMARY KEY,
+  tenant_id INT NOT NULL,
+  name VARCHAR(255),
+  email VARCHAR(255),
+  ...
+  INDEX(tenant_id)
+);
+```
+
+**Pros:**
+
+- Simplest and most cost-effective approach
+- Easier maintenance - single database to back up, monitor, and update
+- Efficient resource utilization
+- Simplified schema management - changes apply to all tenants
+
+**Cons:**
+
+- Risk of data leaks between tenants if queries aren't properly filtered
+- Limited tenant isolation
+- Performance can be affected by "noisy neighbors"
+- One-size-fits-all approach limits customization per tenant
+
+### Pattern 2: Shared Database, Separate Schemas
+
+This pattern uses a single database but creates a separate schema for each tenant.
+
+```sql
+-- Create schema for Tenant 1
+CREATE SCHEMA tenant1;
+
+-- Create tables in Tenant 1's schema
+CREATE TABLE tenant1.customers (
+  id INT PRIMARY KEY,
+  name VARCHAR(255),
+  email VARCHAR(255),
+  ...
+);
+
+-- Create schema for Tenant 2
+CREATE SCHEMA tenant2;
+
+-- Create tables in Tenant 2's schema
+CREATE TABLE tenant2.customers (
+  id INT PRIMARY KEY,
+  name VARCHAR(255),
+  email VARCHAR(255),
+  ...
+);
+```
+
+**Pros:**
+
+- Better separation between tenants while still sharing database resources
+- Lower risk of data leaks compared to shared tables
+- Cost-effective - still only one database to manage
+- Supports tenant-specific customizations
+
+**Cons:**
+
+- Schema migrations must be applied to each tenant schema
+- Database object limits may become an issue with many tenants
+- Resource contention still possible at the database level
+- Backup/restore complexity increases
+
+### Pattern 3: Database-per-Tenant
+
+In this pattern, each tenant gets their own dedicated database.
+
+```sql
+-- Create Tenant 1's database
+CREATE DATABASE tenant1;
+
+-- Create Tenant 2's database
+CREATE DATABASE tenant2;
+```
+
+**Pros:**
+
+- Maximum tenant isolation
+- Easier customization per tenant
+- No "noisy neighbor" problems
+- Simpler compliance with data residency requirements
+- Easier to scale individual tenants
+
+**Cons:**
+
+- Highest operational complexity
+- Most expensive in terms of resources
+- Schema migrations must be applied across all tenant databases
+- Resource underutilization for smaller tenants
+- Database connection management becomes more complex
+
+## Schema Migration Challenges with Multiple Tenants
+
+Schema migration is one of the biggest challenges when dealing with multi-tenant architectures, especially with the database-per-tenant approach:
+
+1. **Version Control**: Keeping track of schema versions across many tenant databases.
+2. **Coordinated Deployment**: Ensuring changes are applied consistently across all tenant databases.
+3. **Rollbacks**: Managing failed migrations becomes exponentially more complex.
+4. **Tenant-Specific Customizations**: Handling deviations in schema between tenants.
+5. **Testing**: Validating migrations across representative tenant databases.
+
+## How to Choose the Right Pattern
+
+When deciding on a multi-tenant architecture, consider these factors:
+
+1. **Number of Tenants**: Shared approaches work well for many small tenants, while database-per-tenant becomes unwieldy with thousands of tenants.
+
+2. **Security Requirements**: If strict data isolation is required (e.g., healthcare, finance), database-per-tenant may be necessary.
+
+3. **Customization Needs**: If tenants need significantly different schemas or configurations, separate databases provide more flexibility.
+
+4. **Operational Resources**: Consider your team's capacity to manage multiple databases versus a single, more complex one.
+
+5. **Scalability Plans**: Think about how your architecture will evolve as you grow from 10 to 100 to 1000+ tenants.
+
+## Hybrid Approaches
+
+Many successful SaaS companies implement hybrid approaches:
+
+- **Tiered Multi-Tenancy**: Small customers in shared infrastructure, premium customers in dedicated databases
+- **Functional Splitting**: Shared databases for common functionality, separate databases for sensitive data
+- **Sharding by Tenant Clusters**: Grouping similar tenants into shared databases
+
+## Managing Schema Migrations in Multi-Tenant Environments
+
+Tools like [Bytebase](https://www.bytebase.com/) can help manage schema migrations across multiple tenant databases by:
+
+1. Providing version control for database schemas
+2. Automating deployment to multiple tenant databases
+3. Offering rollback capabilities when migrations fail
+4. Enforcing schema consistency across tenants
+5. Supporting database branching for tenant-specific customizations
+
+## Conclusion
+
+There's no universal "right answer" to multi-tenant database architecture. The best approach depends on your specific requirements, the nature of your application, and your operational capacity. Many companies start with a shared model for simplicity and cost efficiency, then evolve to more isolated models as they grow and their requirements change.
+
+Whatever pattern you choose, having a robust strategy for schema migrations is essential. This becomes even more critical as your tenant base grows, making tools that can manage schema changes across multiple databases increasingly valuable.