How to Design Multitenant SQL Database Architectures

In today’s software - as - a - service (SaaS) landscape, multitenancy has become a crucial concept. A multitenant application serves multiple customers (tenants) using a shared infrastructure. When it comes to databases, designing a multitenant SQL database architecture allows for efficient resource utilization, reduced costs, and simplified management. In this blog, we will explore the fundamental concepts, usage methods, common practices, and best practices for designing multitenant SQL database architectures.

Table of Contents

  1. Fundamental Concepts
  2. Usage Methods
  3. Common Practices
  4. Best Practices
  5. Code Examples
  6. Conclusion
  7. References

Fundamental Concepts

What is Multitenancy?

Multitenancy refers to a software architecture where a single instance of an application serves multiple customers, known as tenants. Each tenant has its own set of data and may have different usage patterns, security requirements, and business rules.

Types of Multitenancy in SQL Databases

  • Single - Database with Tenant ID: In this approach, all tenant data is stored in a single database. Each table has an additional column, usually named tenant_id, which is used to distinguish between different tenants’ data. For example, if you have a customers table, it will have a tenant_id column to identify which tenant each customer belongs to.
  • Separate Schemas per Tenant: A database can have multiple schemas. Each tenant gets its own schema within the same database. Schemas act as containers for database objects like tables, views, and stored procedures. This approach provides a logical separation of data between tenants.
  • Separate Databases per Tenant: Here, each tenant has its own dedicated database. This offers the highest level of isolation between tenants but may be more resource - intensive in terms of database management and infrastructure.

Usage Methods

Querying Data in a Single - Database with Tenant ID Model

When using the single - database with tenant ID model, all queries must include a WHERE clause to filter data based on the tenant ID. For example, in a SELECT statement to retrieve all customers for a specific tenant:

SELECT * FROM customers WHERE tenant_id = 1;

Working with Schemas

If you are using the separate schemas per tenant model, you need to specify the schema name when accessing database objects. For example, to select all rows from a products table in a tenant’s schema named tenant_1:

SELECT * FROM tenant_1.products;

Managing Separate Databases

When dealing with separate databases per tenant, you need to establish connections to different databases based on the tenant. In a programming language like Python using the psycopg2 library for PostgreSQL:

import psycopg2

tenant_db_name = 'tenant_1_db'
conn = psycopg2.connect(
    database=tenant_db_name,
    user='your_user',
    password='your_password',
    host='your_host',
    port='your_port'
)

Common Practices

Data Partitioning

Data partitioning can be used to improve the performance of a multitenant database. For example, you can partition tables based on the tenant ID. In PostgreSQL, you can use range partitioning:

-- Create a partitioned table
CREATE TABLE orders (
    order_id SERIAL,
    tenant_id INT,
    order_date DATE
) PARTITION BY RANGE (tenant_id);

-- Create a partition for tenant 1
CREATE TABLE orders_tenant_1 PARTITION OF orders
    FOR VALUES FROM (1) TO (2);

Indexing

Proper indexing is essential, especially in the single - database with tenant ID model. Indexing the tenant_id column can significantly speed up queries that filter data by tenant.

CREATE INDEX idx_tenant_id ON customers (tenant_id);

Backup and Recovery

Establish a backup and recovery strategy for each tenant. In the separate databases per tenant model, you can perform individual database backups. For the single - database and separate schemas models, you can backup the entire database or use logical backups to export only the relevant data for each tenant.

Best Practices

Security

  • Data Isolation: Ensure that tenants’ data is isolated from each other. In the single - database with tenant ID model, strict access controls should be in place to prevent unauthorized access to other tenants’ data.
  • Authentication and Authorization: Implement strong authentication mechanisms for tenants. Each tenant should have its own set of credentials, and access to the database should be based on proper authorization rules.

Scalability

  • Horizontal Scaling: Consider horizontal scaling techniques such as sharding. You can shard data based on the tenant ID to distribute the load across multiple database servers.
  • Vertical Scaling: For individual databases or schemas, you can vertically scale by increasing the resources (CPU, memory, storage) of the database server.

Monitoring

Monitor the performance of the multitenant database closely. Keep track of key metrics such as query response times, resource utilization, and the number of concurrent connections per tenant. Tools like Prometheus and Grafana can be used for monitoring and visualization.

Code Examples

Single - Database with Tenant ID Example

-- Create a customers table with tenant ID
CREATE TABLE customers (
    customer_id SERIAL,
    customer_name VARCHAR(100),
    tenant_id INT
);

-- Insert some sample data
INSERT INTO customers (customer_name, tenant_id) VALUES ('John Doe', 1);
INSERT INTO customers (customer_name, tenant_id) VALUES ('Jane Smith', 2);

-- Query data for tenant 1
SELECT * FROM customers WHERE tenant_id = 1;

Separate Schemas per Tenant Example

-- Create a new schema for tenant 1
CREATE SCHEMA tenant_1;

-- Create a products table in the tenant 1 schema
CREATE TABLE tenant_1.products (
    product_id SERIAL,
    product_name VARCHAR(100)
);

-- Insert data into the tenant 1 products table
INSERT INTO tenant_1.products (product_name) VALUES ('Product A');

-- Query data from the tenant 1 products table
SELECT * FROM tenant_1.products;

Conclusion

Designing a multitenant SQL database architecture requires careful consideration of various factors such as data isolation, performance, security, and scalability. By understanding the fundamental concepts, using the right usage methods, following common practices, and implementing best practices, you can create a robust and efficient multitenant database system. Whether you choose the single - database with tenant ID, separate schemas per tenant, or separate databases per tenant model, each has its own advantages and trade - offs that need to be evaluated based on your specific requirements.

References