Difference & Similarities between DBMS and RDBMS
DBMS (Database Management System) and RDBMS (Relational Database Management System) are essential tools in modern computing for efficiently managing and organizing large amounts of data. They serve as the foundation for various applications and systems that require structured data storage and retrieval.
What is DBMS and RDBMS ?
DBMS (Database Management System): A DBMS is a software application that provides an interface for users and applications to interact with databases. Its primary purpose is to store, retrieve, update, and manage data efficiently. DBMS systems offer various features, such as data integrity, security, data modeling, and query optimization. However, DBMSs are not limited to relational databases and can handle other data models like hierarchical or network databases as well.
Types of DBMS
- Relational database.
2. Object oriented database.
- It is a system where information or data is represented in the form of objects which is used in object-oriented programming.
- It is a combination of relational database concepts and object-oriented principles.
- Relational database concepts are concurrency control, transactions, etc.
- OOPs principles are data encapsulation, inheritance, and polymorphism.
- It requires less code and is easy to maintain.
- For example − Object DB software.
3. Hierarchical database.
It is a system where the data elements have a one to many relationship (1:N). Here data is organized like a tree which is similar to a folder structure in your computer system.
- The hierarchy starts from the root node, connecting all the child nodes to the parent node.
- It is used in industry on mainframe platforms.
For example − IMS(IBM), Windows registry (Microsoft).
4. Network database.
A Network database management system is a system where the data elements maintain one to one relationship (1: 1) or many to many relationship (N: N).
It also has a hierarchical structure, but the data is organized like a graph and it is allowed to have more than one parent for one child record.
Example: Teachers can teach in multiple departments.
RDBMS (Relational Database Management System): An RDBMS is a specific type of DBMS that is based on the relational model of data. In the relational model, data is organized into tables with rows and columns, and relationships between tables are established using keys. RDBMSs provide a structured way to store and retrieve data, ensuring data integrity, enforcing constraints, and supporting complex queries through a language like SQL (Structured Query Language).
Popular examples of RDBMS :
- MySQL
- PostgreSQL
- Oracle Database
- Microsoft SQL Server
- IBM Db2
Why we use DBMS and RDBMS ?
1. Data Organization and Management:
- DBMS and RDBMS provide structured ways to organize and manage data. They allow users to define, create, update, and delete data with ease, ensuring data integrity and consistency.
2. Data Integrity:
- RDBMS enforces data integrity constraints, such as primary keys, foreign keys, and unique constraints, to ensure that data remains accurate and valid.
3. Data Security:
- DBMS and RDBMS offer security features like access control, user authentication, and authorization, helping protect sensitive data from unauthorized access and potential breaches.
4. Data Sharing and Collaboration:
- DBMS and RDBMS facilitate data sharing and collaboration among multiple users and applications. Different users can access and modify data concurrently, while the system ensures data consistency.
5. Data Redundancy and Duplication Prevention:
- DBMS and RDBMS help minimize data redundancy by providing mechanisms to store data in a centralized manner. This reduces the risk of inconsistencies that can arise when data is duplicated across multiple files or systems.
6. Data Querying and Reporting:
- DBMS and RDBMS offer query languages (e.g., SQL) that allow users to retrieve specific data subsets based on their requirements. This enables efficient data analysis and reporting.
7. Scalability:
- DBMS and RDBMS are designed to handle large amounts of data, and they provide mechanisms for scaling up the system as data volume increases.
8. Data Recovery and Backup:
- DBMS and RDBMS support data backup and recovery mechanisms to protect against data loss due to hardware failures, crashes, or other unforeseen events.
9. Data Analysis and Decision-Making:
- Organizations can leverage the structured data stored in DBMS and RDBMS to perform data analysis, gain insights, and make informed business decisions.
10. Application Development:
- DBMS and RDBMS are integral to many application development processes, serving as the backend data storage and retrieval systems for a wide range of software, from web applications to enterprise systems.
Key Differences:
DBMS: It may use various data models beyond the relational model, such as the document model, key-value model, or graph model.
RDBMS: It strictly adheres to the relational model, organizing data into tables with well-defined relationships.
Data Integrity and Constraints:
DBMS: Constraints might be limited or not enforced as rigorously as in an RDBMS.
RDBMS: Ensures data integrity by enforcing constraints like primary keys, foreign keys, unique keys, and referential integrity.
Query Language:
DBMS: The query language might be specific to the data model it supports (e.g., SQL-like language for some NoSQL databases).
RDBMS: Typically uses SQL (Structured Query Language) as the standard language for querying and manipulating data.
Scalability:
DBMS: May offer more flexible and dynamic scalability options suitable for certain use cases, such as big data processing.
RDBMS: Often provides vertical scalability (scaling up resources of a single server) and has well-defined methods for data normalization.
In summary, a DBMS is a broader concept encompassing various systems that manage data, while an RDBMS is a specific type of DBMS that uses a relational model to organize and store data in tables with well-defined relationships.