Search Implementation — From Postgres to Algolia

Users expect search to just work. They type a few characters, see instant results, tolerate typos, and find what they're looking for without thinking about it. Google trained the entire world to expect search to be fast, forgiving, and intelligent.

Building search that meets those expectations is harder than it looks. A basic WHERE name LIKE '%query%' gets you surprisingly far, but it falls apart with typos, relevance ranking, and performance at scale. Let's explore the spectrum from simple database queries to dedicated search engines.

Level 1: Basic Database Search

The simplest approach uses SQL pattern matching. It works fine for small datasets:

// Simple ILIKE search — case-insensitive pattern matching
const { data } = await supabase
  .from('products')
  .select