How do storage methods differ for various types of indexes in a database?

Different types of indexes in databases are stored and organized differently to optimize data search and update.

• B-Tree indexes — the most common type. Stored as a balanced tree, where each node contains keys and references to child nodes. This allows for quick search, insertion, and deletion of records with logarithmic complexity.

• Hash indexes — use hash tables for fast access based on exact key matches. Usually stored as arrays with a hash function that determines the position of a record. Not suitable for range queries.

• Bitmap indexes — used for columns with a small number of unique values. Stored as bit vectors, where each bit corresponds to a record and indicates the presence of a value. Effective for analytical queries.

• Full-text indexes — stored as inverted indexes, where each word corresponds to a list of documents or records in which it appears.

Thus, storage methods depend on the data structure and the goals of indexing, which affect the performance of read and write operations.