Tree vs. Graph

The key difference between tree and graph is that tree is a hierarchical data structure that have only one path between vertices whereas graph is a network data structure that can have many paths between vertices.

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Tree vs. Graph

Data structures are one of the most important t concepts in computer programming. Tree and graph are very important data structures both are very different form each other. The tree is a hierarchical data structure that has only one path between vertices whereas graph is a network data structure that can have many paths between vertices. Tree and graph are non-linear data structures. The tree structure can never have loops, and in the case of the graph there can be the loops.

There are finite data items that are known as nodes. In a tree, data is arranged in a sorted order that’s why it is called a non-linear data structure. There is a hierarchical data structure in a tree. There are many kinds of data elements that are organized into branches. Loops are formed in the addition of a new edge in a tree. There are many types of tree that are a binary tree, binary search tree, and AVL tree, threaded binary tree, B-tree and many more. There are many applications of the tree such as data compression, file storage, manipulation of the arithmetic expression and game tree. There is only one node at the top of the tree that is known as the root of the tree. All the remaining data nodes are divided into subtree. There is a height of any tree that is calculated. There must be a path between all the roots of the tree that make it connected. Tree does not have a loop. Terminal node, edge node, level node, degree node, depth, forest are some important terminologies in the tree.  A graph is a non-linear data structure. There are a group of vertices that are also known as a node in the graph. F(v,w) represent vertices. There are many types of graphs such as directed, non-directed, connected, non-connected, simple and multi-graph. If we talk about the application of graphs than a computer network, transportation system, social network graph, electarical circuits and project planning are some well-known examples of graph data structure. Using edge vertex in the graph can be connected. Edge in the graph can also be bidirected the or directed. Where the height of the tree is calculated, in graph edge can be weighted. Adjacent vertices, path, cycle, degree, connected graph, weighted graph are  one of the  important terms in the graph.

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Comparison Chart

BasisTreeGraph
BasisThe tree is a hierarchical data structure that has only one path between verticesThe graph is a network data structure that can have mana y paths between vertices.
Loops There are no loops in the treeThere can be loops in the graph
Cthe omplexImplementation of the tree is less complex than the graphImplementation of the graph is more complex than a tree.
ModelTree is hierarchical modelGraph is network model

Tree

There are finite data items that are known as nodes. In a tree, data is arranged in a sorted order that’s why it is called a non-linear data structure. There is a hierarchical data structure in a tree. There are many kinds of data elements that are organized into branches. Loops are formed in the addition of a new edge in a tree. There are many types of tree that are a binary tree, binary search tree, and AVL tree, threaded binary tree, B-tree and many more. There are many applications of the tree such as data compression, file storage, manipulation of the arithmetic expression and game tree. There is only one node at the top of the tree that is known as the root of the tree. All the remaining data nodes are divided into subtree. There is a height of any tree that is calculated. There must be a path between all the roots of the tree that make it connected. The tree does not have a loop. Terminal node, edge node, level node, degree node, depth, forest are some important terminologies in the tree.

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Graph

 A graph is a non-linear data structure. There are a group of vertices that are also known as a node in the graph. F(v,w) represent vertices. There are many types of graphs such as directed, non-directed, connected, non-connected, simple and multi-graph. If we talk about the application of graphs than a computer network, transportation system, social network graph, electrical circuits and project planning are some well-known examples of graph data structure. Using edge vertex in the graph can be connected. Edge in the graph can also be bidirected or directed. Where the height of the tree is calculated, in graph edge can be weighted. Adjacent vertices, path, cycle, degree, connected graph, weighted graph are some important terms in the graph.

Key Differences

  1. The tree is a hierarchical data structure that has only one path between vertices whereas Graph is a network data structure that can have many paths between vertices.
  2. There are no loops in tree whereas There can be loops in the graph.
  3. Implementation of the tree is less complex than graph whereas Implementation of the graph is more complex than a tree.
  4. The tree is a hierarchical model whereas Graph is a network model

Conclusion

In this article above we see the clear difference between the two most important data structure that is tree and graph with implementation.

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Explanatory Video

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