The decision tree is a very popular classifier technique, making it easy to interpret and visualize the models. It is based on trees. It divides or splits the nodes on the basis of the attribute value and the leaves of the tree usually fall to the majority class classifier. In streaming data, the Hoeffding tree is a very fast algorithm for decision trees; it waits for new instances, instead of reusing instances. It builds a tree for large data. The Concept-adapting Very Fast Decision Tree (CVFDT) deals with the concept of drift, which maintains a model consistency with the instances in a sliding window. The other trees are the Ultra Fast Forest of Trees (UFFT), the Hoeffding adaptive tree, the exhaustive binary tree, and so on.