The Power of Database Indexing Algorithms: B-Tree vs. Hash Indexing

Database indexing is a critical component of optimizing the performance of any database system. Without effective indexing, your database queries can become slow and inefficient, leading to a poor user experience and decreased productivity. In this post, we’ll explore some best practices for creating and using database indexes

There are several indexing algorithms used in databases to improve query performance. Here are some of the most commonly used indexing algorithms:

B-Tree Indexing:

A B-tree index is a self-balancing tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree index structure is widely used in databases and file systems. B-Tree indexing is widely used in relational databases such as MySQL and PostgreSQL.

B-tree indexes are optimized for range queries because they can efficiently find all records within a range of values. This is because the records are stored in sorted order in the index. Leverages to use column comparisons in expressions that use the =, >, >=, <, <=, or…