How do indexing strategies improve database performance, and what are the trade-offs?

Interview Answer:

Indexes accelerate database read operations by creating auxiliary data structures—often B-trees or hash tables—that allow efficient lookup of rows without scanning the entire table. For example, an index on a column like email enables the database to locate records in logarithmic time rather than performing a linear search. This significantly improves performance for SELECT queries, JOINs, and sorting operations.

However, indexes introduce notable trade-offs. They consume additional disk space, increasing storage requirements, especially for large tables. Indexes also slow down write operations—INSERT, UPDATE, DELETE—because each modification must update the associated index structures. Over-indexing can degrade performance rather than improve it.

Choosing the right indexing strategy involves understanding query patterns. Indexes perform best on columns with high selectivity, frequently used in WHERE clauses, JOIN conditions, or ORDER BY operations. Composite indexes should be designed with the leftmost-prefix rule in mind.

In summary, indexes significantly improve query performance but must be used judiciously to balance the cost of space and write overhead.