DBMS
DBMS Part-1
- DBMS Introduction
- DBMS Architecture
- Database Approach vs Traditional File System
- Advantages of DBMS
- Data Models in DBMS
- Schemas in DBMS
- Instances in DBMS
- Data Independence in DBMS
- Database Languages in DBMS
- Interfaces in DBMS
- Structure of DBMS
- Functions of DBA and Designer
- Entities and Attributes in DBMS
- ER Diagram in DBMS
- Generalization, Specialization and Aggregation in DBMS
- Converting ER Diagram to Tables in DBMS
- Difference between Object Oriented, Network and Relational Data Models
DBMS Part-2
- Relational Data Model in DBMS
- Keys in DBMS
- SQL Introduction
- DDL(Data Definition Language)
- DML(Data Manipulation Language)
- Integrity Constraints in DBMS
- Complex SQL Queries
- Joins in DBMS
- Indexing in DBMS
- Triggers in DBMS
- Assertions in DBMS
- Relational Algebra in DBMS
- Tuple Relational Calculus in DBMS
- Domain Relational Calculus in DBMS
DBMS Part-3
- Introduction to Normalization in DBMS
- Normal Forms in DBMS
- Functional Dependency in DBMS
- Decomposition in DBMS
- Dependency Preserving Decomposition in DBMS
- Lossless Join Decomposition in DBMS
- Problems with Null Values and Dangling Tuples
- Multivalued Dependency in DBMS
- Query Optimization in DBMS
- Algorithms for Select, Project and Join Operations in DBMS
- Query Optimization Methods in DBMS
DBMS Part-4
- Transactions in DBMS
- Serializability in DBMS
- Recoverability in DBMS
- Recovery Techniques in DBMS
- Log Based Recovery in DBMS
- Checkpoint in DBMS
- Deadlock in DBMS
- Concurrency Control in DBMS
- Lock Based Protocol in DBMS
- Timestamp Based Protocol in DBMS
- Validation Based Protocol in DBMS
- Multiple Granularity in DBMS
- Multi-Version Concurrency Control(MVCC) in DBMS
- Recovery with Concurrent Transactions in DBMS
DBMS Part-5
Data Independence in DBMS
Data Independence kya hota hai?
Simple shabdon mein:
Data Independence ka matlab hai – database ke ek level ka change, doosre level ko effect na kare.
Iska fayda yeh hai ki hum database ka structure ya storage method change kar sakte hain bina users ya applications ko disturb kiye.
Database ko manage karna aasan ho jata hai aur flexibility badh jati hai.
Data Independence zaroori kyun hai?
Socho agar tumhare database mein thoda sa bhi change karne par, 100+ applications ko bhi update karna pade — kitna headache ho jayega!
Data Independence se:
Database ke andar changes aasani se kar sakte hain.
Users aur programs ko changes ke baare mein kuch nahi karna padta.
Simple mein: Database andar se badle, lekin users ko fark na pade!
Types of Data Independence
Data Independence ke do types hote hain:
Type | Meaning | Example |
---|---|---|
1. Logical Data Independence | Jab logical schema (tables ka design) change karne se users aur applications ko koi effect nahi hota. | Table mein naye column add karna. |
2. Physical Data Independence | Jab data ki storage ka method change karne se tables ya logical structure ko koi effect nahi hota. | Data ko ek naye fast hard disk pe shift karna. |
Diagram se samjho:
External Level: Jo users dekhte hain.
Logical Level: Tables aur relations ka structure.
Physical Level: Data disk par kaise store hota hai.
Simple Real-Life Example
Ek library ka example lo:
Physical Level: Books shelves mein rakhi hain.
Logical Level: Book catalog (title, author, ISBN ke sath).
External Level: User computer pe search karta hai “Harry Potter”.
Ab agar:
Staff books ko naye shelves mein shift kar de (physical change) — Users ko koi farak nahi padta! (physical data independence)
Nayi “Genre” information add kar di catalog mein — Search karne ka tareeka same rahta hai! (logical data independence)
Practical Example DBMS mein:
Logical Data Independence Example:
Student table:
Student_ID | Name | Course |
---|
Kal hum ismein ek aur column add kar dete hain: Phone_Number
.
Student_ID | Name | Course | Phone_Number |
---|
Students ka app waise ka waisa kaam karta hai.
Old queries jaise:
SELECT Name, Course FROM Student;
- abhi bhi bilkul sahi chalti hain.
Physical Data Independence Example:
Maan lo:
Student records pehle ek HDD (hard disk) mein the.
Ab hum unhe ek naye SSD (faster drive) pe move kar dete hain.
Lekin students ko ya applications ko koi farak nahi padta.
Quick Comparison Table:
Feature | Logical Data Independence | Physical Data Independence |
---|---|---|
Changes in | Table ka design | Data ka storage |
Affects | User ka view | Table structure |
Example | New column add karna | Data ko doosre disk pe shift karna |
Important Points:
Schema change hona ≠ Users ko problem hona.
Storage change hona ≠ Tables ya programs ka change hona.
Database zyada flexible aur easy to maintain ho jata hai.
Final Summary:
Term | Meaning | Example |
---|---|---|
Logical Data Independence | Structure badle, user unaffected | New column add |
Physical Data Independence | Storage badle, table unaffected | Move data to SSD |