Single Database per Client vs. Multi-Tenant Architecture: Understanding the Trade-Offs

Typically, web applications with many users store all their data in a single database. This is a multi-tenant approach, where tenants (clients in your case) share the same database schema (structure).

Here's where the idea of a single database per client comes in. It's a different approach where each client gets their own dedicated database.

Advantages of a Single Database per Client

Things to Consider

Choosing the Right Approach

The decision depends on factors like:

• Security requirements
• Number of clients
• Expected data growth
• Budgetary constraints

This code snippet showcases a simplified way to manage client information:

clients = [
    {"id": 1, "name": "Client A"},
    {"id": 2, "name": "Client B"},
]

def get_client_database_name(client_id):
  """Returns a database name based on client ID"""
  return f"client_{client_id}"

This creates a list of clients and a function to generate a database name based on the client ID. You'd likely store client data in a more robust way (e.g., database) in a real application.

Database Creation (SQL):

This pseudocode demonstrates creating a database using SQL:

CREATE DATABASE IF NOT EXISTS {database_name};

This code snippet checks if the database exists and creates it if not. You'd replace {database_name} with the actual name generated from the Python function.

Code Integration:

Imagine you have a function to insert data into a table. Here's how you might integrate client-specific databases:

def insert_data(client_id, data):
  # Get database name
  database_name = get_client_database_name(client_id)

  # Connect to the specific database
  # (connection details omitted for brevity)
  connection = connect_to_database(database_name)
  cursor = connection.cursor()

  # Insert data using the cursor (specific SQL statement omitted)
  cursor.execute(...)

  # ... (commit changes, close connection)

This code retrieves the database name, connects to it, and then uses a cursor to execute the data insertion logic specific to your application.

• Implementation:

  • Add a client_id column to every table in the database.
  • Modify queries to filter data based on the client_id of the current user or client.
  • Enforce data access controls to ensure users can only access data belonging to their assigned client(s).

Multi-tenancy with Row Level Security (RLS):

• • Define policies within the database that limit which rows a user can see based on their credentials or associated client ID.
  • The database enforces these policies automatically, ensuring users only see relevant data.

The best method depends on your specific needs. Here's a brief comparison:

• • Simpler to implement initially.
  • Might require complex queries to handle data relationships across tables.
  • Data isolation is achieved through application logic, potentially introducing security risks if not implemented carefully.

• Multi-tenancy with RLS:

  • More secure data isolation by leveraging database features.
  • Might require additional configuration and expertise in RLS functionalities.
  • Can potentially impact performance depending on the complexity of the policies.