PostgreSQL uses indexes to boost data retrieval speeds by reducing the amount of data the database reads from disk. This is especially useful for queries that don't return a large percentage of a table; typically, indexes are most effective when fetching less than 15-20% of the rows. The article highlights that while indexes improve performance, they come with tradeoffs, including additional disk space usage and overhead during data modification operations like inserts and updates. The piece explains how PostgreSQL stores data on disk in a structure called a heap, which consists of 8 KB pages. Each row in the heap has an associated tuple ID (TID). When querying data without an index, PostgreSQL performs a sequential scan, reading every row, which can be inefficient. In a demonstration, searching for a specific name without an index took over 265 milliseconds. After creating an index on the name column, the same query executed in just 0.077 milliseconds, highlighting the dramatic speed improvement. The article lists six default index types available in PostgreSQL and notes that the index itself is a tree structure linking key values to their corresponding row locators. It emphasizes the importance of considering the costs associated with maintaining indexes, including increased disk space and potential slowdowns when data is modified. Understanding these factors allows developers to make informed decisions about when and how to implement indexes for optimal database performance.