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| DBMS Complete Notes in Hindi |
DBMS (Database Management System) : DBMS Tutorial Notes
Go through these DBMS notes to find all the important concepts in a decent explanation for better knowledge on database systems
Learn the basics of DBMS in simple and easy steps starting from its introduction to advanced concepts with examples including DBMS Architecture, Advantages and Disadvantages of DBMS, Importance of DBMS, and more.
Learn about the layers and components of DBMS architecture and how they work with each other for efficient data management
General Topics of DBMS for Placement help you to face the technical interview and technical assessment tests.
Get (Database Management System) DBMS notes for RPSC Programmer DBMS notes for RPSC Programmer, Important points and problem solving methods are prepared in dbms notes which are here
Index About DBMS:
- What is Data, Database, DBMS
- Data, Information, Knowledge
- File System v/s DBMS
- Database Model
- Database Architecture
- 3-Schema Architecture
- RDBMS (Relational Database Management System)
Database Keys
- Candidate Key
- Primary Key
- Secondary Key
- Super Key
- Foreign Key
- Prime Attribute
- Non-prime Attribute
- Simple Candidate Key
- Composite/Complex Candidate Key
Normalization Basics – Normal Form
Normalization is a process of organizing data in a database to reduce redundancy and improve data integrity.
- 1NF (First Normal Form)
- 2NF (Second Normal Form)
- 3NF (Third Normal Form)
- BCNF (Boyce-Codd Normal Form)
SQL (Structured Query Language) - RDBMS से Communicate करने के लिए |
- DDL (Data Definition Language)
- DML (Data Manipulation Language)
- TCL (Transaction Control Language)
- DCL (Data Control Language)
Indexing in Database
Indexing improves the speed of data retrieval operations on a database table.
Transactions in Database (ACID Properties)
Transactions in databases should comply with ACID properties for reliable processing.
- A = Atomicity
- C = Consistency
- I = Isolation
- D = Durability
Data | Database | DBMS
Data: Raw data or raw facts like names, places, or scores.
- Example: Sonu, Jaipur, 89
- Characteristics: Unstructured, unorganized.
Database: A collection of inter-related data.
- Structured: Data stored in a fixed structure.
- Example: RDBMS (Relational Database Management System)
- Unstructured: Data not in a fixed structure.
- Example: NoSQL, Big Data (e.g., Hadoop)
DBMS: Application software that performs operations on the database.
Data, Information, and Knowledge
Data: Raw data or raw facts
| Unstructured |
| unorganized |
Information: After processing data, we get meaningful information.
Example:
| Name | City | Marks |
|---|---|---|
| Sonu | Jaipur | 89 |
Knowledge: After processing information, we gain insights or knowledge.
- Example: Class topper's name by analyzing the information.
Database Overview
Structured Database: Data organized in a predefined structure. Typically used in sectors where data size is limited and organized.
- Applications: Banking sector, finance sector, Indian Railways, college databases
- Data transaction: Structured and managed transactions
- Examples:
- Oracle - Oracle Corporation
- MySQL
- SQL Server - Microsoft
- MS Access - Microsoft
- DB2 - IBM
Unstructured Database: Data with large and variable size, typically used in less organized or flexible formats.
- Applications: Social media platforms, delivery services (e.g., Swiggy, Zomato), e-commerce (e.g., Flipkart, Amazon)
- Examples:
- NoSQL databases:
- MongoDB
- Cassandra
- Neo4j
- HBase
- CouchDB
- Elastic Search
File System vs. Database
| File System | Database |
|---|---|
| Managed by the operating system. | 1. Manages large data sizes (GB, TB). |
| Data redundancy (duplication). | 2. Typically more costly to implement and maintain. |
| Data inconsistency issues. | 3. Serves as an interface between users and database files. |
| Data access can be difficult. | 4. Ensures data atomicity and isolation. |
| manage small ammount of data sizes (KB, MB). |
Database Architecture
3-schema Architecture
Schema: Database का overall logical representation है। यह database के design का representation है।
Schemas:
- External Schema: View Level
- User के लिए different-different schemas होते हैं।
- Example: College database के लिए, अलग-अलग users connect होते हैं:
- Student
- Faculty
- Team
- HOD
- Conceptual Schema: Logical Level (What data stored in database)
- यह database के logic को define करता है। यह RDBS में table या tables के relationship को define करता है।
- Physical Schema: Internal Level (How data stored in DB file)
- It defines how data is actually stored in database files.
- Database files और data dictionary maintain करते हैं।
Schema and Instance
Schema:
यह overall logical representation है।
Instance:
Database में किसी particular time पर stored data की database instance कहते हैं।
Database का snapshot @ particular point of time।
Database instance frequently change होता रहता है।
Schema Levels:
- View Level: External Schema - Logical Data Independence
- Conceptual Level: Conceptual Schema - Logical Data Independence
- Internal Level: Physical Schema - Physical Data Independence
- DB File
Logical Data Independence:
Database के logical schema में changes करने पर, tables के बीच relationships change करने का effect कभी भी external schema independence पर नहीं होता है।
Physical Data Independence:
Database के physical structure में change करने का logical या view-level independence पर कोई effect नहीं पड़ता है।
Example: New Hard Disk Add करना
Database Model
- Hierarchical data model: (Old)
- Network data model: (Old)
- Relational data model: → Relation - table
- Object-Oriented data model:
- Object-Relational model:
- Entity-Relationship data model: → database की graphic design करने के लिए
