Priority Queue vs Heap

Updated April 18, 2023

Introduction to Priority Queue vs Heap

• The priority queue and heap are different types of data structure and works to operate data.
• The priority queue and heap is works on data structure sorting and implementing the path of the queue.
• The priority queue and heap are correlated with each other for working on the queue and sorting data.
• The heap and priority queue use algorithm help to implement priority queue and sorting data.
• The priority queue is the queue data structure and the heap is the tree data structure that operates and organizes data.
• The priority queue is based on a queue data structure working as a queue with a priority function.
• The heap is a tree data structure uses for sorting data in a specific order using an algorithm.
• The priority queue is working on the queue and the heap is working on the tree data structure.
• The priority queue and heap are used in object-oriented technology to operate data of the web applications.

Head to Head Comparison Between Priority Queue vs Heap (Infographics)

Below are the top 13 differences between Priority Queue vs Heap:

Comparison Table

• The priority queue works on the queue data structure and the heap works on the tree data structure.
• The priority queue and heap are used in the object-oriented languages to operate and sorted the data of the applications.
• The heap is working to implement and sort the priority queue as per the requirement of the priority or order.
• The priority queue and heap have several similarities as well as differences.
• This data structure depends on many conditions with their unique types and properties.

The comparison table of the priority queue and heap shows below.

Function	Priority queue	Heap
Definition	The priority queue is working on the queue and the heap is working on the tree data structure.	The heap is a tree data structure uses for sorting data in a specific order using an algorithm.
Base	It is based on the queue structure.	It is based on the tree data structure.
Rules	Queue with priority function.	Parent and child node.
Function	The priority queue works as a queue but extra function priority works on the element.	The heap works as a binary tree and the parent and child node works on the element.
Types	The priority queue has two types. ·         Max priority queue ·         Min priority queue	The heap has two types. ·         Max heap ·         Min heap
Structure	·         The priority queue looks like the basic queue structure of the value. ·         The priority queue is stored array value in a simple form.	·         The heap looks like the tree structure of the value. ·         The heap is stored array value in a sorted form.
Description of the types	·         The max priority works in descending order. ·         The min priority works in ascending order.	·         The max heap works in descending order. ·         The min-heap works in ascending order.
Operations	The priority queue provides the following operations. ·         The “is_empty” operation checks the queue is empty or not. ·         The “insert_with_priority” operation inserts elements in the queue with a given priority. ·         The “pull_highest_priority_element” operation removes an element from the queue with a given priority.	The heap provides the following operations. ·         The “is_empty” operation checks the queue is empty or not. ·         The “insert”, “extract”, “delete”, and “replace” operation works with the value and node. ·         The “shift_up” and “shift_down” operations move the node top and bottom of the heap structure. ·         The “size” operation given available elements in the heap. ·         The “merge” and “meld” operations work for joining two heaps.
Implementation	The priority queue implements element with the array. ·         The array value or list of values place as a queue. ·         The priority function adds to operate queue value as per the priority of the value. ·         You can use priority queue operations and types on the data.	The heap implements elements with the array. ·         The array value represents a node of the tree or heap. ·         The array element crates the parent and child node. ·         You can use heap operations and types on the data.
Algorithm	The priority queue uses in the following algorithm. ·         Dijkstra’s algorithm ·         Huffman coding ·         A best-first search algorithm ·         ROAM triangulation algorithm ·         Prim’s algorithm	The heap uses in the following algorithm. ·         Selection algorithm ·         Dijkstra’s shortest path algorithm ·         Prim’s minimal spanning tree algorithm.
Applications	The priority queue uses for the following purposes. ·         The priority queue maintains and manages the bandwidth of the transmission line. ·         The priority queue adds discrete events with simulation time. ·         The insertion and deletion of the priority queue with the highest and lowest priority.	The heap uses for the following purposes. ·         The insertion and deletion of the heap value with the highest and lowest priority. ·         The heap creates or implements the priority queue as an abstract data type. ·         The heap searches the smallest and largest element of the given array.
Languages	The priority queue uses in C++, Java, Scala, Go, and PHP programming languages.	The heap uses in C++, Java, Perl, Go, Python, and PHP programming languages.
Uses	The priority queue uses for abstract data type and its function.	The heap uses for abstract data type and its function.

Key Differences

• The priority queue is working on the queue and the heap is working on the tree data structure.
• The priority queue is stored array value in a simple form while the heap is stored array value in a sorted form.
• The heap provides multiple functions and operations than the priority queue. The priority queue provides queue-related functions.
• The heap implements abstract data types such as priority queue but priority queue does not implement heap.
• The priority queue is simpler than the heap data structure. the heap is complicated because of the parent node rule.

Conclusion

• The priority queue data structure and heap data structure create, operate, and organizes the array data.
• The priority queue and heap works on the highest and lowest priority of the array value.
• The priority queue and heap maintains large scale, complicated data of the application easily.

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