docs: multi-tenant database architecture patterns

Author: tianzhou

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

@@ -1,27 +1,30 @@
 ---
 title: Multi-Tenant Database Architecture Patterns Explained
 author: Tianzhou
-updated_at: 2025/03/15 10:00:00
+updated_at: 2025/03/18 10:00:00
 feature_image: /content/blog/multi-tenant-database-architecture-patterns-explained/banner.webp
-tags: Explanation, Hidden
+tags: Explanation
 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.
+We frequently hear from prospects about their schema migration challenges. One of the top 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:
+When building a SaaS application, determining the optimal database architecture for multi-tenancy is a pivotal decision that significantly influences scalability, security, cost-efficiency, and operational complexity. The architectural spectrum ranges from shared-everything models, where tenants share databases, schemas, and tables, to shared-nothing approaches, where each tenant has dedicated resources.
 
-- **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/):
 
-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).
+![reddit](/content/blog/multi-tenant-database-architecture-patterns-explained/reddit.webp)
+
+and has sparked a lot of tears in [HackerNews](https://news.ycombinator.com/item?id=23305111):
+
+![hn](/content/blog/multi-tenant-database-architecture-patterns-explained/hn.webp)
 
 ## Multi-Tenant Database Architecture Patterns
 
 Let's explore the common patterns for multi-tenant database architectures:
 
-### Pattern 1: Shared Everything
+### Pattern 1: Shared Everything - Shared Database, Shared Schema
 
 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.
 
@@ -40,18 +43,22 @@ CREATE TABLE customers (
 
 - 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"
+- 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
 
+<HintBlock type="info">
+
+Only applicable to database engines supporting separate schemas like PostgreSQL, SQL Server.
+
+</HintBlock>
+
 This pattern uses a single database but creates a separate schema for each tenant.
 
 ```sql
@@ -120,50 +127,73 @@ CREATE DATABASE tenant2;
 - Resource underutilization for smaller tenants
 - Database connection management becomes more complex
 
-## Schema Migration Challenges with Multiple Tenants
+### Summary
+
+| Dimension                  | Shared Database, Shared Schema                                         | Shared Database, Separate Schemas            | Database per Tenant                            |
+| -------------------------- | ---------------------------------------------------------------------- | -------------------------------------------- | ---------------------------------------------- |
+| **Database Support**       | ✅ All database systems                                                | ❓ PostgreSQL, SQL Server, Oracle            | ✅ All database systems                        |
+| **Regulatory Compliance**  | ❌ Most difficult for strict compliance needs                          | ❓ May meet requirements with careful design | ✅ Easiest to meet data residency requirements |
+| **Operational Complexity** | ✅ Low; simplest deployment model                                      | ❌ High; one instance, many schemas          | ❌ High; many instances to manage              |
+| **Schema Customization**   | ❌ Difficult; typically requires Entity-Attribute-Value (EAV) patterns | ❌ Limited customization possible            | ✅ Complete freedom per tenant                 |
+| **Scalability**            | ❌ Must scale entire database                                          | ❌ Must scale entire database                | ✅ Can scale individual tenants                |
+
+We recommend avoiding the **Shared Database, Separate Schemas** approach because it introduces complexity comparable to **Database per Tenant** without offering sufficient isolation to meet stringent regulatory compliance requirements.
+
+When starting your greenfield project, the **Database per Tenant** model should only be chosen if your business demands strict regulatory compliance in day 1.
+
+![decision-flow-chart](/content/blog/multi-tenant-database-architecture-patterns-explained/decision-flow-chart.webp)
+
+In summary, our guidance is to adopt the **Shared Database, Shared Schema** approach whenever possible. Only transition to **Database per Tenant** if compliance, scalability, or customization requirements necessitate it. Avoid **Shared Database, Separate Schemas**, as it combines the drawbacks of both models without delivering significant benefits.
+
+## Schema Migration Best Practices with Multiple Tenants
 
-Schema migration is one of the biggest challenges when dealing with multi-tenant architectures, especially with the database-per-tenant approach:
+Schema migrations are inherently challenging, and if you opt for the **Database per Tenant** model, the complexity increases significantly:
 
-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.
+1. **Change History**: Keeping track of schema versions across many tenant databases.
+1. **Coordinated Deployment**: Ensuring changes are applied consistently across all tenant databases.
+1. **Rollbacks**: Managing failed migrations becomes exponentially more complex.
+1. **Tenant-Specific Customizations**: Handling deviations in schema between tenants.
+1. **Testing**: Validating migrations across representative tenant databases.
 
-## How to Choose the Right Pattern
+To tackle this, you should adopt best practices:
 
-When deciding on a multi-tenant architecture, consider these factors:
+1. **Version Control for Migration Scripts**
 
-1. **Number of Tenants**: Shared approaches work well for many small tenants, while database-per-tenant becomes unwieldy with thousands of tenants.
+   - Store all migration scripts in version control systems
+   - Use sequential versioning (e.g., V1, V2) or timestamp-based versioning
+   - Never modify committed migration scripts
 
-2. **Security Requirements**: If strict data isolation is required (e.g., healthcare, finance), database-per-tenant may be necessary.
+1. **Automated SQL Analysis in CI Pipeline**
 
-3. **Customization Needs**: If tenants need significantly different schemas or configurations, separate databases provide more flexibility.
+   - Configure SQL linters to run on every migration script
+   - Block PRs that introduces risky patterns by failing the CI pipeline
 
-4. **Operational Resources**: Consider your team's capacity to manage multiple databases versus a single, more complex one.
+1. **Idempotent Migrations**
 
-5. **Scalability Plans**: Think about how your architecture will evolve as you grow from 10 to 100 to 1000+ tenants.
+   - Design migrations to be safely re-runnable
+   - Include checks like `IF NOT EXISTS` for table creation
+   - Use transactions where possible to ensure atomicity
 
-## Hybrid Approaches
+1. **Staged Rollout Strategy**
 
-Many successful SaaS companies implement hybrid approaches:
+   - Test migrations on development/staging environments first
+   - Deploy to a small subset of tenants (canary deployment)
+   - Monitor for issues before full deployment
 
-- **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
+1. **Backward Compatibility**
 
-## Managing Schema Migrations in Multi-Tenant Environments
+   - Design schema changes to support both old and new application versions
+   - Consider using database views for compatibility layers
+   - Implement multi-phase migrations for breaking changes
 
-Tools like [Bytebase](https://www.bytebase.com/) can help manage schema migrations across multiple tenant databases by:
+1. **Tenant Metadata Registry**
 
-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
+   - Maintain a central registry of all tenant databases
+   - Track current schema version for each tenant
+   - Record migration history and status
 
-## Conclusion
+<HintBlock type="info">
 
-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.
+Bytebase offers [batch change](/docs/change-database/batch-change/), [SQL Review](/docs/sql-review/overview/), [GitOps](/docs/vcs-integration/overview/) to streamline and simplify schema migrations for the **Database per Tenant** model.
 
-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.
+</HintBlock>