Why access control protects sensitive data in Snowflake - Performance Analysis

Time Complexity: Why access control protects sensitive data

O(n)

Understanding Time Complexity

We want to understand how the time to check access rights grows as more users or data are involved.

How does the system handle more requests while keeping data safe?

Scenario Under Consideration

Analyze the time complexity of the following access control check in Snowflake.

-- Check if user has access to a table
SELECT HAS_ACCESS(
  CURRENT_USER(),
  'DATABASE_NAME',
  'SCHEMA_NAME',
  'TABLE_NAME'
);
    

This operation checks if the current user has permission to access a specific table.

Identify Repeating Operations

When many users request access, the system repeats:

• Primary operation: Permission lookup for each user and object.
• How many times: Once per access request.

How Execution Grows With Input

As the number of access requests grows, the system checks permissions for each request separately.

Input Size (n)	Approx. API Calls/Operations
10	10 permission checks
100	100 permission checks
1000	1000 permission checks

Pattern observation: The number of permission checks grows directly with the number of access requests.

Final Time Complexity

Time Complexity: O(n)

This means the time to verify access grows in a straight line as more requests come in.

Common Mistake

[X] Wrong: "Checking access once means all future requests are instantly allowed."

[OK] Correct: Each request is checked separately to keep data safe, so time grows with requests.

Interview Connect

Understanding how access control scales helps you design secure systems that handle many users smoothly.

Self-Check

"What if access checks were cached per user? How would the time complexity change?"