在B+树中，由于只有指针存储在内部节点中，因此它们的大小明显小于B树的内部节点(存储数据+键)。 因此，B+树的索引可以在一次磁盘读取中从外部存储中提取，处理后找到目标的位置。如果它是一个B树，那么每个决策过程都需要读取磁盘。希望我把我的观点讲清楚了!：）

下图有助于显示B+树和B树之间的区别。

B+树的优点:

Because B+ trees don't have data associated with interior nodes, more keys can fit on a page of memory. Therefore, it will require fewer cache misses in order to access data that is on a leaf node. The leaf nodes of B+ trees are linked, so doing a full scan of all objects in a tree requires just one linear pass through all the leaf nodes. A B tree, on the other hand, would require a traversal of every level in the tree. This full-tree traversal will likely involve more cache misses than the linear traversal of B+ leaves.

B树的优点:

因为B树包含每个键的数据，所以经常访问的节点可以位于更靠近根的位置，因此可以更快地访问。

数据库系统概念示例

B+树

相应的b -树

In a B tree search keys and data are stored in internal or leaf nodes. But in a B+-tree data is stored only in leaf nodes. Full scan of a B+ tree is very easy because all data are found in leaf nodes. Full scan of a B tree requires a full traversal. In a B tree, data may be found in leaf nodes or internal nodes. Deletion of internal nodes is very complicated. In a B+ tree, data is only found in leaf nodes. Deletion of leaf nodes is easy. Insertion in B tree is more complicated than B+ tree. B+ trees store redundant search keys but B tree has no redundant value. In a B+ tree, leaf node data is ordered as a sequential linked list but in a B tree the leaf node cannot be stored using a linked list. Many database systems' implementations prefer the structural simplicity of a B+ tree.

举个例子——你有一个每一行都有大量数据的表。这意味着对象的每个实例都是大的。

如果在这里使用B树，那么大部分时间都花在扫描带有数据的页面上——这是没有用的。在数据库中，这就是使用B+树来避免扫描对象数据的原因。

B+树将键和数据分开。

但如果你的数据量比较小，你可以用键来存储它们就像B树那样。

由于终端节点形成了一个链表，B+树更容易进行全面扫描，而且性能更高，可以查看树索引的每一块数据。要使用B-Tree进行完整扫描，您需要进行完整的树遍历以查找所有数据。

另一方面，当您执行seek(按键查找特定数据段)时，B-Trees可以更快，特别是当树驻留在RAM或其他非块存储中时。由于可以提升树中常用的节点，因此获取数据所需的比较较少。