I found this page (Memory locality & the magic of B-Trees!) on B-Trees as a very interesting read and, would recommend anyone and everyone to go through it to quickly understand the nuances of B-Tree.
B-Tree could be defined as a linked sorted distributed range array with predefined sub array size which allows searches, sequential access, insertions and deletions in logarithmic time.
Simply speaking, B-Tree is nothing but the generalization of a Binary Search Tree. One may recall that the nodes in a Binary Search Tree could have just one key and a maximum of two child nodes. However, a B-Tree could have nodes having multiple keys (more than one) and, more than two child nodes. Following diagram represents a B-Tree of order 5.
Following are some of the key points discussed later in this article:
Following represents features of B-Tree:
Thus, given some of the above disadvantages, what is needed is a data structure which achieves the primary objectives of faster search, faster sequential access and, faster insertion and deletion operations. This is where B-Tree fits in. Following is how indexes get stored and searched in the B-Tree.
A key is always inserted into the leaf node of the B-Tree. However, to make sure that all leaf remains at the same level, the tree grows upward adding nodes at a level lesser than the level of the leaf node. Following is how the insertion happens in the B-Tree given that there is only a root node present in the B-Tree.
Following are some good pages on B-Trees that I came across on the internet:
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