What are indexes and how do they speed up searches in relational databases?

Indexes in relational databases are special data structures stored separately from the main tables and used for fast searching of rows by given criteria. Without indexes, the database has to perform a full scan of the entire table to find the required record, which takes a lot of time on large amounts of information. Using the right indexes can reduce query execution times from minutes to milliseconds.

The most common type of index is the B-tree. This structure organizes data in the form of a balanced search tree, which allows finding the necessary elements in logarithmic time. In addition to B-trees, there are other types, such as hash indexes for exact matches, as well as specialized indexes for spatial data and full-text search.

Understanding how composite indexes work is critical for effective database design. A composite index includes several fields of a single table. When creating it, the order of the columns is of decisive importance, because the database can use the index only when the query involves columns starting from the first one.

It is important to remember that indexes are not a universal solution to all performance problems. Each additional index speeds up read operations, but slows down write operations, such as inserting, updating, and deleting rows. This happens because the DBMS is forced to update not only the table itself, but also all associated indexes with every data modification.

The process of choosing indexes should be based on the actual usage profiles of the application. Developers should index fields that frequently participate in search conditions, joins, and sorts, while avoiding the creation of redundant structures that waste disk space and reduce the overall speed of the system.