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B-Tree is an indexing technique most commonly used in databases and file systems where pointers to data are placed in a balance tree structure so that all references to any data can be accessed in an equal time frame. It is also a tree data structure which keeps data sorted so that searching, inserting and deleting can be done in logarithmic amortized time.
The B-Tree belongs to a group of techniques in computer science known as self-balancing search trees which attempts to automatically keep the number of levels of nodes under the root small at all times. It is the most preferred way to implement sets, associative arrays and other data structures that are used in computer programming languages, relational database management systems and low level data manipulations.
A B-tree is a specialized multiway tree designed especially for use on disk. In a B-tree each node may contain a large number of keys. The number of subtrees of each node, then, may also be large. A B-tree is designed to branch out in this large number of directions and to contain a lot of keys in each node so that the height of the tree is relatively small. This means that only a small number of nodes must be read from disk to retrieve an item. The goal is to get fast access to the data, and with disk drives this means reading a very small number of records. Note that a large node size (with lots of keys in the node) also fits with the fact that with a disk drive one can usually read a fair amount of data at once.
A multiway tree of order m is an ordered tree where each node has at most m children. For each node, if k is the actual number of children in the node, then k - 1 is the number of keys in the node. If the keys and subtrees are arranged in the fashion of a search tree, then this is called a multiway search tree of order m. For example, the following is a multiway search tree of order 4. Note that the first row in each node shows the keys, while the second row shows the pointers to the child nodes. Of course, in any useful application there would be a record of data associated with each key, so that the first row in each node might be an array of records where each record contains a key and its associated data. Another approach would be to have the first row of each node contain an array of records where each record contains a key and a record number for the associated data record, which is found in another file
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