differences between Graphs and Trees? [excluded Graphical Concept]

Topic	Graph	Tree
Rules & Restriction:	In general graph doesn’t really have any rules and restrictions.	Tree is the restricted specialized version of graph with numerous rules specially how to connect nodes.
Direction :	Graph can have Uni-directional or Bi-directional paths between nodes.	Tree has linear direction (only one path between each two vertices) that comes along with “Parent-children” relationship. *point to be noted: one child can have only one parent (as it is in real.)
Circles and all :	Can be cyclic (or acyclic) or have loop, circuit and self loop.	Tree doesn't have any circles back or self loop or circuit or cycles.
Recursive Data :	No such thing.	Tree is Recursive Data Structure due to the nodes with children.
DAG:	Can only be cyclic or acyclic	Tree fits within the category of Directed Acyclic Graphs in short DAG (graph that has no cycles).
Complexity:	Graphs are more complex due to all the loops and cycles it got.	Trees are really easy to understand.
Connection:	In graph objects connects themselves by Links. *in mathematical abstractions it calls Vertices or in between same pair it calls edges.	Tree is actually Minimally connected graph. In easy English its: one path between each two vertices.
Outlook:	It’s more likely a diagrammatic overview.	It’s more likely a flow looking overview. (e.g. flow chart)
Root node:	No such thing.	Exactly only one root node.
Parent child relation:	No such thing.	In tree, there is parent child relationship for the sake of flow so there can be the direction top to bottom or vice versa.
Traversal kinds:	Graph traversed by DFS (depth First Search) and BFS (Breadth First Search) algorithm.	3 types: a. Pre order b. In order c. post order *all of these are in DFS or BFS algo.
Different types:	Basically only two types can be highlighted: a. Directed graph b. Undirected graph	There are actually too many. Like, Binary tree, Binary Search Tree, AVL tree, Heaps etc.
Number of edges:	No boundary.	Always have to have n-1 numbers of edges.
Model type:	Network model.	Hierarchical model