This document provides an overview of relational database management systems (RDBMS). It discusses why databases are useful, particularly for storing related data about students, courses, and professors in an organized way. Using a RDBMS avoids issues like data loss that could occur without transactions when multiple users simultaneously access and update large datasets. The document then covers database design principles, accessing databases with SQL, and compares RDBMS to non-relational databases. RDBMS provide ACID transactional consistency while non-RDBMS scale out more easily but have weaker consistency models.

1. S
RELATIONAL DATABASE
MANAGEMENT SYSTEMS
(RDBMS)
Levon Khachatryan:
Database Developer

2. What they have in common?

3. Agenda
S Why to use databases?
S Database design importance
S Accessing RDBMS with SQL
S RDBMS vs. Not RDBMS

4. Why to use databases?
Suppose we are building a system to store the information about:
S students
S courses
S professors
S who takes what
S who teaches what

5. Can we do it without RDBMS?
Sure we can!
Start by storing the data in files:
S students.txt
S courses.txt
S professors.txt

6. Doing it without a RDBMS...
Our Task: Enroll “Mary Sargsyan” in “Programming”:
S Write a program to do the following:
1. Read ‘students.txt’
2. Read ‘courses.txt’
3. Find and update the record ‘Mary Sargsyan’
4. Find and update the record ‘Programming’
5. Write ‘students.txt’
6. Write ‘courses.txt’
Write ‘Students.txt’

7. Possible Issues
1. Lost connection
2. Large datasets (say 50GB)
3. Simultaneous access by many users

8. Why we don’t have this issues in
RDBMS?
S A transaction = sequence of statements that either all
succeed, or all fail
S Transactions have the ACID properties:
A = atomicity
C = consistency
I = isolation
D = durability

9. ACID
S Automicity: Each transaction is unique and make sure that if one logical
part of a transaction fails everything is rollbacked so that data are
unchanged.
S Consistency: All data written to the database are subject to the rules
defined (constraints, triggers, etc.)
S Isolation: Changes made in a transaction are not visible to other
transactions until they are committed.
S Durability: Changes committed in a transaction are stored and available in
the database even if there is power failure or the database goes offline
suddenly.

10. The most popular RDBMS
1. MS SQL Server
2. PostgreSQL
3. Oracle
4. DB2

11. Database design importance
Databases cause
90% of application
performance issues.

12. S Google has 3.5 billion searches
per day, which is 40,000 search
queries every second
S Amazon has 310 million active
users
Database design importance

13. Database design examples:
Solution 1

14. Database design examples:
Solution 1

15. Database design examples:
Solution 2

16. Accessing RDBMS with SQL
SQL – Structured Query
Language
S DML – Data manipulation language
S DDL – Data Definition Language

17. Categories of Non-relational
databases
S Key-values database: This is the simplest form of NoSQL database
where each value is associated with unique key.(ex Redis)
S Column database: This database is capable of storing and processing
large amount of data using a pointer that points to many columns
that are distributed over a cluster.(ex HBase)
S Document database: This database can contain many key-values
documents with many nested level. Efficient Querying is possible
with this database. The documents are stored in JSON format.(ex
MongoDB)
S Graph database: Instead of traditional rows and columns, this
databases uses nodes and edges to represent graph structures and
store data.(ex Neo4J)

18. RDBMS vs. Not RDBMS
ADVANTAGES
1. They support ACID transactional consistency and support joins.
2. Relationships in this system have constraints
3. Strong SQL
1. Relational Databases do not scale out horizontally very well (CAP Theorem)
2. Data is normalized, meaning lots of joins, which affects speed
3. They have problems working with semi-structured data
DISADVANTAGES
RDBMS

19. RDBMS vs. Not RDBMS
NOT RDBMS
ADVANTAGES
1. They scale out horizontally and work with unstructured and semi-
structured data
2. Mostly are open source and so free
1. Weaker or eventual consistency (BASE) instead of ACID
2. Limited support for joins
3. Does not have built-in data integrity (must do in code).
DISADVANTAGES

20. THANK YOU
Synergy International Systems