Caching vs Database Indexing

Same data requested repeatedly

Product pages, user profiles, search results, API responses. Anything multiple users (or the same user) request often.

Data doesn't change frequently

If your product catalog updates once a day, there's no reason to query the database on every page load

Pages get slower as your data grows

If a page loaded fine last month but crawls now, a full table scan on a growing table is the most likely cause

You filter, sort, or search on a specific column

Any column that shows up in a WHERE clause, ORDER BY, or search query is a candidate for an index. If users filter orders by status, index the status column

A single query takes over 200ms

For most web apps, a database query should take under 50ms. If Django Debug Toolbar shows a query taking hundreds of milliseconds, an index is the first thing to try

Data must always be real-time

Live stock prices, real-time chat messages, collaborative editing. Stale data here means broken features.

Every request is unique

If every query has different parameters and no patterns repeat, caching just wastes memory with zero hits

Your table has very few rows

With under 1,000 rows, the database can scan the whole table in microseconds. Adding an index won't make a noticeable difference and just adds overhead on every insert

The column has very few unique values

Indexing a column that only holds True or False doesn't help much. The database still has to read half the table. Indexes shine on columns with many unique values, like user IDs or email addresses

You write far more than you read

Every index slows down inserts and updates slightly, because the database has to update the index too. For write-heavy tables (like a high-volume log), adding many indexes can hurt more than it helps