Why Database Indexes Are the Secret Weapon for Faster Queries

Anyone who has done server‑side development knows a program can run without a database index, yet most tutorials devote a lot of space to indexes, and interviewers often ask about them. This article, the first in a series on database indexes, explains what an index is and why it matters.

What is a database index?

Understanding composite (joint) indexes

20‑minute index design practice

Why indexes are implemented with B+ trees

What is a database index?

A database index is a technique that speeds up queries on massive data sets. Think of it like the table of contents in a dictionary that lets you locate a word quickly instead of scanning every page.

What is a composite (joint) index?

A composite index includes multiple columns, e.g., INDEX idx_test(col_a, col_b). Using the dictionary analogy, it’s like using both the radical and stroke count to locate a character, narrowing the search range step by step.

Left‑most prefix matching

For a composite index, the query can use the index only up to the first column that is not referenced or is used in a range condition. For example, with INDEX idx_i1(col_a, col_b), a query filtering only on col_b cannot use the index, while a query filtering on col_a (and optionally col_b) can.

What is a clustered index?

When the index determines the physical order of the data, it is a clustered index; all other indexes are non‑clustered. In MySQL InnoDB, the primary key is the clustered index, whereas MyISAM has no clustered index.