DBMS Concepts

DBMS Tutorial Components of DBMS. Applications of DBMS The difference between file system and DBMS. Types of DBMS DBMS Architecture DBMS Schema Three Schema Architecture. DBMS Languages.

DBMS ER Model

ER model: Entity Relationship Diagram (ERD) Components of ER Model. DBMS Generalization, Specialization and Aggregation.

DBMS Relational Model

Codd’s rule of DBMS Relational DBMS concepts Relational Integrity Constraints DBMS keys Convert ER model into Relational model Difference between DBMS and RDBMS Relational Algebra DBMS Joins

DBMS Normalization

Functional Dependency Inference Rules Multivalued Dependency Normalization in DBMS: 1NF, 2NF, 3NF, BCNF and 4NF

DBMS Transaction

What is Transaction? States of transaction ACID Properties in DBMS Concurrent execution and its problems DBMS schedule DBMS Serializability Conflict Serializability View Serializability Deadlock in DBMS Concurrency control Protocols

Difference

Difference between DFD and ERD

Misc

Advantages of DBMS Disadvantages of DBMS Data Models in DBMS Relational Algebra in DBMS Cardinality in DBMS Entity in DBMS Attributes in DBMS Data Independence in DBMS Primary Key in DBMS Foreign Key in DBMS Candidate Key in DBMS Super Key in DBMS Aggregation in DBMS Hashing in DBMS Generalization in DBMS Specialization in DBMS View in DBMS File Organization in DBMS What Is A Cloud Database What Is A Database Levels Of Locking In DBMS What is RDBMS Fragmentation in Distributed DBMS What is Advanced Database Management System Data Abstraction in DBMS Checkpoint In DBMS B Tree in DBMS BCNF in DBMS Advantages of Threaded Binary Tree in DBMS Advantages of Database Management System in DBMS Enforcing Integrity Constraints in DBMS B-Tree Insertion in DBMS B+ Tree in DBMS Advantages of B-Tree in DBMS Types of Data Abstraction in DBMS Levels of Abstraction in DBMS 3- Tier Architecture in DBMS Anomalies in Database Management System Atomicity in Database Management System Characteristics of DBMS DBMS Examples Difference between Relational and Non-Relational Databases Domain Constraints in DBMS Entity and Entity set in DBMS ER Diagram for Banking System in DBMS ER Diagram for Company Database in DBMS ER Diagram for School Management System in DBMS ER Diagram for Student Management System in DBMS ER Diagram for University Database in DBMS ER Diagram of Company Database in DBMS Er Diagram Symbols and Notations in DBMS How to draw ER-Diagram in DBMS Integrity Constraints in DBMS Red-Black Tree Deletion in DBMS Red-Black Tree Properties in DBMS Red-Black Tree Visualization in DBMS Redundancy in Database Management System Secondary Key in DBMS Structure of DBMS 2-Tier Architecture in DBMS Advantages and Disadvantages of Binary Search Tree Closure of Functional Dependency in DBMS Consistency in Database Management System Durability in Database Management System ER Diagram for Bank Management System in DBMS ER Diagram for College Management System in DBMS ER Diagram for Hotel Management System in DBMS ER Diagram for Online Shopping ER Diagram for Railway Reservation System ER Diagram for Student Management System in DBMS Isolation in DBMS Lossless Join and Dependency Preserving Decomposition in DBMS Non-Key Attributes in DBMS Data Security Requirements in DBMS DBMS functions and Components What is Homogeneous Database? DBMS Functions and Components Advantages and Disadvantages of Distributed Database

Advantages and Disadvantages of Binary Search Tree

Binary search trees (BSTs) are a type of data structure that allow for efficient search, insertion, and deletion of elements. In a Binary Search Tree, the elements are organized in a hierarchical structure, with the root node at the top and the leaves at the bottom. The elements in each node are organized in such a way that the element in the left child is always less than the element in the parent node, and the element in the right child is always greater than the element in the parent node.

Some of the features of Binary Search Tree are given below:

  • A BST is a binary tree, which means that each node in the tree has at most two children.
  • In a BST, the value of each node in the left subtree of the root is less than the value of the root, and the value of each node in the right subtree is greater than the value of the root.
  • A BST is a dynamic data structure, which means that it can change over time as elements are inserted and deleted.
  • The height of a BST is the number of edges from the root to the farthest leaf. A BST with n nodes has a height of O (log n), which makes it relatively efficient for search and insertion/deletion operations.
  • A BST is not necessarily a balanced tree, which means that the height of the tree may not be uniform across all nodes. An unbalanced tree can lead to longer search times.
  • The in-order traversal of a BST produces a sorted list of the elements in the tree.
  • BSTs are often used to implement associative arrays, which allow for fast search and insertion/deletion of elements based on a key value.

Advantage of binary search tree:

  • One advantage of BSTs is that they can be searched faster than other data structures, such as linear data structures like arrays and linked lists, because they are organized in a specific way.
  • The organization of elements in BST allows for faster search because, in order to find an element in the Binary Search Tree, you can eliminate half of the elements in the tree at each step by comparing the element you are searching for to the element in the current node.
  • Binary Search Trees are relatively easy to implement and use. Inserting and deleting elements in a BST is also relatively efficient.
  • it is easy to find the appropriate position for the new element based on its value and the organization of the tree.

Overall, the main advantages of BSTs are that they allow for fast search, insertion, and deletion of elements, which make them a useful data structure in many applications.

Disadvantage of Binary Search Tree:

There are a few potential disadvantages of using a binary search tree (BST) as a data structure:

  • A BST is not necessarily a balanced tree, which means that the height of the tree may not be uniform across all nodes. An unbalanced tree can lead to longer search times, as the worst-case time complexity for search in a BST is O (n), where n is the number of nodes in the tree.
  • Insertion and deletion operations in a BST have a time complexity of O(h), where h is the height of the tree. In an unbalanced tree, h can be as large as n, so insertion and deletion can be slower in an unbalanced BST compared to a balanced tree.
  • BSTs require more memory than other data structures, such as arrays and linked lists, because each node in the tree must store two pointers (to the left and right children) in addition to the element itself.
  • BSTs are not well suited for real-time systems because the time complexity for search and insertion/deletion is not guaranteed to be constant.
  • BSTs are not stable, which means that the order of the elements in the tree may change as elements are inserted and deleted. This can be a disadvantage if the order of the elements is important.

Overall, while BSTs have some advantages, they may not be the best choice for every situation due to their potential for unbalanced trees and their time and space complexity for certain operations.