Difference Between b tree and b+ tree

By BYJU'S Exam Prep

Updated on: September 25th, 2023

Difference Between B Tree and B+ Tree: B trees and B+ trees are used to store the records in sorted order on a disk. The major difference between B Tree and B+ Tree is that a B tree has an internal index structure while a B+ Tree has two pointers to its own node (one for each child node) and an extra pointer pointing to its parent node. 

B trees and b+ trees are two types of general data structures used in computer science. This article will teach you the difference between a B-tree and a B+ tree. We will also discuss how these two types of trees can be used to speed up sorting and searching operations on large data sets.

Difference Between B Tree and B+ Tree

Both B trees and B+ trees are used for storing the records in sorted order on a disk. However, they have different features that make them more efficient than the other one. 

Differentiate Between B Tree and B+ Tree

B Tree B+ Tree
B Tree is used to sort the data with various fascilities such as insertion, deletion, search, etc. B+ Tree is the modified version of B Tree providing all the funcitons smoothly and quickly.
Both Internal nodes and leaf nodes are used to store Records and Keys. Keys are stored in Internal node whereas records stored in leaaf nodes.
No duplication is allowed. Duplication may occur.
Linking of leaf nodes is not done with each other. Linking of leaf nodes is done with each other.
Speed of searching is not as quick as compared to B+ Tree. Speed of searching is very quick.
Sequential access is not possible. Sequential access is possible.

What is B Tree?

The B-tree is a generalization of a binary search tree in that a node can have more than two children. A B-tree is a tree data structure that keeps data sorted and allows searches, insertions, and deletions in logarithmic amortized time.

The key difference between standard trees and B trees is that while a standard tree provides only one path from the root node (the top level) down through branches into leaves, B trees can have multiple paths from root nodes down through branches into leaves. This means there are more ways for you to get from one point in your data set to another

A B-tree stores data in sorted order on disk, using pointers to point to each record’s location. A key attribute is that it’s an efficient implementation for storage and retrieval which can maintain this ordering property across generations of the tree (i.e., multiple files).

What is a B+ Tree?

A B+ tree is an N-ary tree with a variable but often a large number of children per node. It’s also a generalization of the B-tree, which has only two properties:

  • Parents can’t have any more children than their number of children

  • All nodes must be either empty or non-empty (i.e., they can’t be both empty and not empty)

A B+ tree has the following structure:

  • Each node contains data items.

  • Nodes are organized in a way that they can be traversed by following their parent pointers or left to right. This means that you can go from one end of the tree to another or start at its root and go down through all its branches until you reach another branch with which it shares a parent pointer (this will happen if there’s no other way). The children of any given node are also stored in this order (concerning their parents).

  • Each node may contain several sub-nodes, where each sub-node contains additional data items (and so forth).

Conclusion of B Tree vs B+ Tree Comparison

There are many different kinds of trees and they each have their own unique features. The B-tree is a perfect example of this because it will allow you to store data in an efficient manner while still allowing you to perform searches quickly and efficiently. This is because there are no duplicates when searching through this type of structure, which means the search process will be much faster than if we were using another type of data structure such as a B+ tree where all nodes would share an equal amount of content at any given time (like how most databases work today).

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