A database management system, commonly referred to as DBMS, is essentially a collection of software programs that interacts with a database to manage, control, retrieve, and maintain data. The DBMS acts as an intermediary between a client and an application program, and it is used to create, define, and manipulate data within a database. Field names, record structures, and record structures are typically managed by the DBMS, and it also defines rules that regulate and manipulate the data in the database. DBMS programs like MySQL, SQL Server, Oracle, dBase, FoxPro, and SQL use query languages to link up with databases and create programs for data inquiry and maintenance.

A database management system receives directives from a database administrator and instructs the database to execute the required commands like sorting, loading, retrieving, or modifying the existing data within the database. The storage elements and data structure may be modified in the database without altering the DBMS program itself. There are four main types of database management systems.

1. Relational Database Management System:

A relational database is a type of database that stores data in a structured manner using tables that are made up of rows and columns. This makes it easy to retrieve and locate specific data in the database. In a relational database, tables within tables are related to each other in a logical manner. The tables containing data are called relations, defined by rows and columns referred to as fields. Each table contains a key field that uniquely identifies each record, which helps to link different tables across the database.

This type of relational structure makes it easy to run queries on multiple tables simultaneously to retrieve the required data. An RDBMS may also provide a graphical view of the data. For instance, it may display data in a spreadsheet-like table, allowing you to see and edit individual data elements within the table. Some RDBMS programs allow you to create forms that can streamline data entry, editing, and deletion. Most database management systems belong to the RDBMS category, which includes Oracle database, MySQL, Microsoft SQL Server, and IBM DB2.

Currently, the relational database approach is the most prevalent. The older hierarchical data management systems are being replaced with relational database management. Relational DBMS software is available for large mainframe systems, workstations, and personal computers. The need for more powerful and flexible data models to support scientific and commercial applications has led to increased relational data models. In this model, table entries are not just simple values but can be programs, text, unstructured data, or any other format that the end-user requires.

Data structured in tables consisting of rows and columns are much easier to manage and retrieve. Information can be stored in separate tables or records that contain logically related values, allowing large amounts of data to be divided, making it easier and faster to manage and retrieve. Different tables from which data needs to be connected and extracted can be easily managed. Security and authorization control can also be implemented more easily by moving sensitive data in a given database to an isolated connection with its own authorization controls. Data independence is easily achieved in a relational database compared to a more complex tree or structured structure. Repetition and duplication of data can be minimized in an RDBMS. It offers the possibility of responding to queries via a language based on relational algebra and relational calculus. It offers seamless database independence, meaning data can be viewed in various ways by different clients. Multiple users can access the database simultaneously, which is not possible in other types of databases. RDBMS also offers much better backup and recovery options.

A major limitation and drawback of RDBMS is its dependence on machine performance. If the number of tables between which relationships need to be established is large, then the performance in responding to the SQL queries is affected. The required hardware is complex and software expensive, increasing the overall cost of implementing RDBMS.

2. Object-Oriented Database Management System:

The Object Oriented (OO) database model combines the principles of object orientation and database management, creating a hybrid system that surpasses conventional relational database management systems. The OO database supports consistency, separation, atomicity, and durability while working with objects in the programming language that mirrors working with objects in the database. Each database object has a unique object identifier (OID), created by the system, which is used to identify the object in memory. Using an OO database boosts application performance, enabling the delivery of any object the application requires to memory. Any update or deletion made to the object occurs in memory and then saved to the database, preventing the need for frequent database visits during upgrades and deletions.

A Hierarchical Database Management System has a one-to-many relationship between data elements (1: N), containing a single root and employing a tree-like structure that connects various components into one parent record. Information in a hierarchical database is stored as records containing single value fields linked together through joins. The structure of a hierarchical database results in the storage of duplicate data that can only be accessed through a specific chain of hierarchy. Hierarchical databases work best when data collection is focused on a specific hierarchy with specific parent-child relationships such as employees in a company and departments or assets.

NoSQL Databases refer to non-SQL or non-relational databases that offer a feature for storing and retrieving data, using methods different from the relational databases. They deliver simplicity in design, easy and flat scaling to clusters of machines, and better control over availability, using different data structures from those used in relational databases. NoSQL databases are appropriated based on the problems they intend to solve, and their data structures are seen as more flexible than relational database tables. MongoDB is an example of NoSQL document-based databases that work well with dynamic schemas.

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