
Multi-Tenant Architecture: Designing SaaS for Data Isolation
Building a platform for multiple enterprise clients? Explore the pros and cons of "Shared Schema" vs. "Database-per-Tenant" for security and scale.
Multi-Tenant Architecture: Designing SaaS for Data Isolation
When building an enterprise SaaS application, such as an ESG reporting platform, one of the most critical architectural decisions revolves around how to implement Multi-Tenancy. Ensuring that "Client A" can never access "Client B’s" data is not merely a feature; it is a fundamental security requirement that influences your entire backend design.
The Shared Schema: Achieving Logical Isolation
The most prevalent approach to multi-tenancy is the Shared Schema. In this model, every table includes a tenant_id column, which simplifies maintenance and reduces costs. However, this strategy places a significant responsibility on developers to consistently remember to include a WHERE clause to enforce data isolation.
To alleviate this risk, especially when using Node.js, consider implementing middleware or Query Hooks at the ORM level (such as Mongoose or Prisma). These tools can automatically inject the tenant_id into every query, effectively creating a "Virtual Private Database."
Database-per-Tenant: Ensuring Physical Isolation
For industries that demand heightened security, like Fintech or Healthcare, the Physical Isolation model is often the preferred choice. In this architecture, each client operates on their own dedicated database, providing superior security and simplifying backup processes. However, this approach introduces significant DevOps challenges, as you must manage migrations across potentially hundreds of databases simultaneously.
To tackle these challenges, leveraging Infrastructure as Code (Terraform) is recommended. This ensures consistency and efficiency across your entire database fleet, making multi-tenant management more streamlined.
Scaling the NoSQL Way: The Collection-per-Tenant Approach
If you're using MongoDB, a viable middle-ground solution is the Collection-per-Tenant strategy. This method offers a level of isolation without the heavy overhead associated with managing multiple database instances. Regardless of the approach you choose, it's crucial to implement a robust Tenant Context in your API.
By resolving the tenant at the very edge of the request—using subdomains or headers—you can create a secure and isolated environment capable of scaling seamlessly from 10 clients to 10,000.
- Utilize Query Hooks to automate tenant isolation in shared schemas.
- Consider physical isolation (DB-per-tenant) for clients with high compliance requirements.
- Automate multi-tenant migrations using Infrastructure as Code for consistency and efficiency.
Continue Reading
You Might Also Like

The Architect's Guide: SQL to NoSQL (Postgres to MongoDB)
Migrating your data layer? Discover the pitfalls of SQL-to-NoSQL migration, from schema redesign to ensuring 100% data consistency.

Designing Stable Java Microservices for Cross-Border Fintech Systems
Cross-border fintech platforms demand extreme reliability and correctness. Learn how Java microservices are designed to handle global payment flows involving banks, MNOs, MTOs, and digital wallets in production environments.

System Design in Practice: From Requirements to Scalable Architecture
Effective system design starts with understanding requirements. Learn how senior engineers translate business needs into scalable architectures using database design, HLD, LLD, and clear documentation.
Need Help With Your Project?
Our team specializes in building production-grade web applications and AI solutions.
Get in Touch