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A Linear data structure have data elements arranged in sequential manner and each member element is connected to its previous and next element. This connection helps to traverse a linear data structure in a single level and in single run. Such data structures are easy to implement as computer memory is also sequential. Examples of linear data structures are List, Queue, Stack, Array etc.

A non-linear data structure has no set sequence of connecting all its elements and each element can have multiple paths to connect to other elements. Such data structures supports multi-level storage and often cannot be traversed in single run. Such data structures are not easy to implement but are more efficient in utilizing computer memory. Examples of non-linear data structures are Tree, BST, Graphs etc.

Following are the important differences between Linear Data Structures and Non-linear Data Structures.

Sr. No. | Key | Linear Data Structures | Non-linear Data Structures | |
---|---|---|---|---|

1 | Data Element Arrangement | In linear data structure, data elements are sequentially connected and each element is traversable through a single run. | In non-linear data structure, data elements are hierarchically connected and are present at various levels. | |

2 | Levels | In linear data structure, all data elements are present at a single level. | In non-linear data structure, data elements are present at multiple levels. | |

3 | Implementation complexity | Linear data structures are easier to implement. | Non-linear data structures are difficult to understand and implement as compared to linear data structures. | |

4 | Traversal | Linear data structures can be traversed completely in a single run. | Non-linear data structures are not easy to traverse and needs multiple runs to be traversed completely. | |

5 | Memory utilization | Linear data structures are not very memory friendly and are not utilizing memory efficiently. | Non-linear data structures uses memory very efficiently. | |

6 | Time Complexity | Time complexity of linear data structure often increases with increase in size. | Time complexity of non-linear data structure often remain with increase in size. | |

7 | Examples | Array, List, Queue, Stack. | Graph, Map, Tree. |

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