Database Indexing

Database indexing creates B-tree or hash-based data structures that allow the database engine to locate rows without performing a full table scan. Without indexes, a query on a table with 1 million rows must examine every single row. With proper indexes, the same query touches only a handful of rows. AI-generated code almost never includes index definitions — queries work fine during development with 100 test records, then grind to a halt with production data volumes. Common indexing mistakes include missing indexes on foreign keys, over-indexing (which slows writes), and missing composite indexes for queries that filter on multiple columns.