What is a database management system (DBMS)?

A few key features of a DBMS are as follows:

• Data storage: Data can be structured, unstructured, or semi-structured. A DBMS should be able to organize and manage data.
• Data retrieval and manipulation: A DBMS allows users to query data with specific query languages such as SQL, PL\SQL, and KQL. Users can run commands such as inserts, updates, and deletes to perform database activities.
• Data integrity and concurrency control: A DBMS includes mechanisms to ensure data is accurate and consistent, and multiple users can work on the data without affecting its consistencies or conflicts.
• Security: A DBMS supports user authentication, authorization, and encryption mechanisms to ensure data is safe and secure while data is at rest or motion.
• Backup and recovery: A DBMS supports database backup and restoration mechanisms to safeguard against data loss or corruption. It should allow data recovery quickly, securely, and safely.
• Consistency: A DBMS ensures data is accurate, consistent, and anomalies-free. Any transaction should be a complete success or failure, not a partial failure or success.
• Indexing: A DBMS supports various indexing mechanisms for faster data retrieval and query performance tuning.

Database Management Systems (DBMS) can be categorized into four categories.

1. Relational Database Management Systems (RDBMS):

• An RDBMS organizes the structured data into tables. A table consists of rows and columns.
• Each table has a pre-defined schema with columns and their data types.
• It allows for setting up relationships among different tables.
• Examples include Microsoft SQL Server, Oracle, and MySQL.

2. NoSQL Database Management System

• A NoSQL DBMS is suitable for handling unstructured data.
• It offers flexible schema and various data models as per data requirements.

1. Document oriented
2. Key value pairs
3. Wide Column databases
4. Graph databases

3. Object-Oriented Database Management System (ODBMS):

• It stores data in the form of objects based on classes.
• It is suitable for handling complex data structures.
• It allows for the creation of classes and inheritance
• Examples include ObjectDB and db4o.

4. Hierarchical Database Management System:

• A hierarchical DBMS organizes data into parent-child relationships like a tree structure.
• Each parent can have multiple children, while each child record has only one parent.
• Example: IBM's Information Management System (IMS)

The choice of a Database Management Systems (DBMS) depends on the data storage, data types, and management requirements.

Here are a few well-known examples:

MySQL: MySQL is a widely used open-source RDBMS. It is known for its speed, reliability, and ease of use. MySQL is often used in web applications and is a vital component of the Linux, Apache, MySQL, PHP/Perl/Python stack.

Microsoft SQL Server: It is Microsoft's database management system suitable for following workloads.

• Online Transaction Processing ( OLTP)
• Online Analytical Processing (OLAP)

Additionally, it offers Reporting Services and Integration Services (ETL), and Azure databases. 

Oracle Database: Oracle’s database is famous for its scalability, robustness, and enterprise features suitable for large and mission-critical applications.

MongoDB: MongoDB is a popular NoSQL database that uses a document-oriented data model. It is designed for flexibility, scalability, and handling of unstructured data. MongoDB is widely used in web and mobile applications.

Neo4j: Neo4j is a graph database that manages and queries data with complex relationships. It is ideal for applications involving social networks, recommendation engines, and knowledge graphs.

Redis: Redis is an open-source, in-memory data store often used as a key-value database or cache. It is known for its high-speed data retrieval and is used to build real-time applications and cache frequently accessed data.

Couchbase: Couchbase is a distributed NoSQL cloud database with unmatched versatility, performance, and scalability for cloud, mobile, AI, and edge computing applications. 

PostgreSQL: PostgreSQL is an open-source RDBMS with high extensibility and SQL compliance. It supports relational (SQL) and non-relational (JSON) queries with increased resilience, correctness, and integrity. It adds support for geospatial, JSON data types, and analytical applications. 

Although it is technically feasible to have a database without a dedicated Database Management System (DBMS), this configuration would be extremely limited in usefulness and efficacy. Generally speaking, a DBMS is essential to effectively managing and maintaining databases. While you can create databases without a DBMS, they would not be feasible for real-time applications that require well-established frameworks for handling data securely, effectively, and scalable with changing data requirements.

SQL refers to the Structure Query Language that communicates with the DBMS. There are various forms of SQL language as per the RDBMS. Here are a few examples:

• Microsoft SQL Server: T-SQL (Transact-SQL)
• Oracle: PL/SQL
• PostgreSQL: pgSQL
• MySQL: MySQL