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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