The primary difference between a B-tree and a B+ tree lies in how they store data and the structure of their nodes:
- Data Storage:
- B-tree: Both internal nodes (non-leaf nodes) and leaf nodes can store actual data records. When you search for a value, you might find it in any node (internal or leaf).
- B+ tree: Only the leaf nodes store actual data records. Internal nodes store only keys to guide the search, making them more efficient for indexing.
- Leaf Nodes:
- B-tree: Leaf nodes are not necessarily linked together.
- B+ tree: Leaf nodes are usually linked in a linked list, making range queries and sequential access more efficient.
- Searching Efficiency:
- B-tree: Search might end at any level, and you may have to search through several nodes, including non-leaf ones, for the data.
- B+ tree: Since data is only stored in leaf nodes and internal nodes act as index points, the search is typically more efficient because you always descend through the same path of internal nodes until you reach a leaf.
- Traversal:
- B-tree: Traversal can be more complex since data can be in both internal and leaf nodes.
- B+ tree: Traversal is simplified since all data is located at the leaf level, and with the linked list connection between leaf nodes, range queries can be more efficient.
In summary, B+ trees are generally preferred for database indexing and file systems because they allow for more efficient searches, sequential access, and range queries. B-trees are still useful, but B+ trees provide better performance for these use cases.