Relational databases manage indexes as a way to optimize query performance and speed up data retrieval. An index in a relational database is a data structure that enhances the speed of operations on a database table. It works similarly to an index in a book: instead of searching through every page, you can look up the index to quickly find the information you need. When a database query is executed, the database can use an index to locate rows with specific values much more efficiently than scanning the entire table.
Creating an index involves specifying one or more columns that you want to index. For example, in a table of customer records, you might create an index on the "last_name" column to speed up queries searching for customers by their last name. The index maintains a sorted list of the values in the indexed column along with pointers to the corresponding rows in the table. When a query is run, the database can quickly navigate through the index, find the relevant rows, and return the results, significantly reducing the amount of time required compared to a full table scan.
However, while indexes improve read performance, they can have some downsides. For example, maintaining an index requires additional storage space, and indexes can slow down write operations, such as inserts, updates, or deletes. This is because the database needs to update the index whenever data changes. As a best practice, developers should consider which columns most frequently appear in search criteria or join conditions and prioritize indexing those. Additionally, it's wise to periodically review and optimize indexes to ensure they continue to provide a net benefit to performance over time.