Caching strategies in Supabase - Time & Space Complexity

Time Complexity: Caching strategies

O(n)

Understanding Time Complexity

When using caching with Supabase, we want to know how the number of data fetches changes as requests grow.

We ask: How does caching affect the number of times we call the database?

Scenario Under Consideration

Analyze the time complexity of fetching user profiles with caching.

// Check if user profile is in cache
const cachedProfile = cache.get(userId);
if (cachedProfile) {
  return cachedProfile; // Use cached data
}
// If not cached, fetch from Supabase
const { data, error } = await supabase
  .from('profiles')
  .select('*')
  .eq('id', userId)
  .single();
cache.set(userId, data); // Store in cache
return data;
    

This code tries to get a user profile from cache first, then fetches from Supabase if missing, and stores it in cache.

Identify Repeating Operations

Look at what happens when many user profiles are requested.

• Primary operation: Database fetch calls to Supabase when cache misses occur.
• How many times: Once per unique user profile not found in cache.

How Execution Grows With Input

As more unique user profiles are requested, the number of database calls grows with the number of misses.

Input Size (n)	Approx. Api Calls/Operations
10	Up to 10 database calls if none cached
100	Up to 100 database calls if none cached
1000	Up to 1000 database calls if none cached

Pattern observation: Without cache hits, calls grow linearly with unique requests; with cache hits, calls reduce greatly.

Final Time Complexity

Time Complexity: O(n)

This means the number of database calls grows directly with the number of unique user profiles requested when cache misses happen.

Common Mistake

[X] Wrong: "Caching makes the number of database calls constant no matter how many users we request."

[OK] Correct: Cache only helps if data is already stored; new unique requests still cause database calls.

Interview Connect

Understanding how caching affects database calls shows you can think about efficiency and user experience in real apps.

Self-Check

"What if we changed the cache to expire every minute? How would the time complexity change when many requests come in quickly?"