We need a separate data structure like B-Trees for databases and file systems for several key reasons:
Efficient storage and retrieval of large amounts of data: B-Trees are optimized for storing and retrieving massive volumes of data from relatively slow storage media like disks and tapes[5]. Traditional data structures like arrays and linked lists are not efficient when dealing with data stored on slow storage systems[5].
Self-balancing property: B-Trees are self-balancing, meaning the maximum and minimum difference in the number of nodes along any path from the root to a leaf node is no more than a factor of two[5]. This ensures the tree is always well-balanced for efficient searching, inserting and deleting[5]. Arrays and linked lists lack this property, requiring additional sorting and searching operations to maintain order[5].
Handling large datasets: B-Trees are designed to handle large datasets that cannot be stored entirely in memory[5]. Traditional approaches may be limited by memory constraints and require additional processes like swapping to manage big datasets[5].
Optimized for disk-based storage: B-Trees excel at managing data on low-speed storage media like disks, mak...
