Forem: MATHAN S

Amazon S3 Explained: Simple Storage in the Cloud

MATHAN S — Thu, 18 Dec 2025 17:31:57 +0000

1)Service Overview
Amazon S3 is an object storage service provided by AWS that allows users to store, retrieve, and manage data such as files, images, videos, backups, and logs. It is highly scalable, secure, and durable.

2)Key Features
Unlimited storage capacity
High durability
Data versioning and lifecycle management
Encryption at rest and in transit
Access control using IAM and bucket policies
Supports static website hosting

3)AWS Category / Cloud Domain
Category: Storage
Cloud Domain: Infrastructure as a Service

4)Where It Fits in Cloud / DevOps Lifecycle
Used for application data storage
Stores build artifacts in CI/CD pipelines
Used for backups and disaster recovery
Stores logs and monitoring data
Hosts static websites in cloud architectures

5)Programming Language / Access Methods
AWS Management Console
AWS CLI
AWS SDKs (Java, Python, JavaScript, Go, .NET)
REST APIs (HTTP/HTTPS)

6)Pricing Model
Pay-as-you-go model
Charged based on:
Amount of data stored
Number of requests
Data transfer out
Free tier available with limited storage and requests

MURAL: A Visual Collaboration Tool in the DevSecOps Periodic Table

MATHAN S — Thu, 18 Dec 2025 17:27:12 +0000

1)Overview of the Tool

MURAL is a digital collaboration and visual workspace tool used by teams to brainstorm, plan, and collaborate in real time using virtual whiteboards. It helps teams visualize ideas through sticky notes, diagrams, flowcharts, and frameworks.

2)Key Features

Real-time collaborative whiteboards
Sticky notes, shapes, flowcharts, and templates
Brainstorming, mind mapping, and design thinking tools
Voting, comments, and facilitation features
Integration with tools like Jira, Microsoft Teams, Slack, and Zoom

3)How It Fits into DevOps / DevSecOps

Helps DevOps teams during planning, sprint retrospectives, and architecture discussions
Useful for threat modeling and security design brainstorming in DevSecOps
Improves collaboration between developers, security teams, and operations
Supports agile ceremonies like stand-ups, retrospectives, and workshops

4)Programming Language

Built using JavaScript
Uses HTML, CSS

5)Parent Company

MURAL (MURAL Inc.)

6)Open Source or Paid

*Not open source
*Paid tool

NORMALIZATION In LiveSQL

MATHAN S — Tue, 07 Oct 2025 10:16:20 +0000

Normalization is one of the most important concepts in database design. In this blog, we’ll walk through normalizing a student-course-instructor dataset step by step — from 1NF to 3NF — using SQL CREATE TABLE and INSERT INTO statements.

Identify Anomalies
Insertion anomaly:
Can’t insert a new course unless a student enrolls.

Update anomaly:
If Dr. Kumar’s phone number changes, we must update multiple rows.

Deletion anomaly:
If student S02 drops the course, we lose info about the DBMS course entirely.

Convert to 1NF (First Normal Form)
Remove repeating groups, ensure atomic values.

Creation of table

Insertion of data

Output

Convert to 2NF (Second Normal Form)

Remove partial dependency (non-key attributes should depend on the whole key).

Create separate tables for Students, Courses, Instructors, Studentcourses.

Create table for Students

Insert values into the table

Output

Create table for Courses

Insertion of values

Output

Create table for Instructors

Insertion of values

Output

Create table for Studentcourses

Insertion of values

Output

Convert to 3NF (Third Normal Form)
Remove transitive dependency (non-key attributes shouldn’t depend on other non-keys).

👉 In our case, the InstructorPhone depends on Instructor, not directly on Course.
So we already separated Instructors, which makes this 3NF compliant.

Final tables in 3NF:

Students(StudentID, StudentName)
Instructors(Instructor, InstructorPhone)
Courses(CourseID, CourseName, Instructor)
StudentCourses(StudentID, CourseID)
Query Using JOINs

Key Takeaway

By breaking down our initial table step by step:

1NF → Atomic values
2NF → Remove partial dependencies
3NF → Remove transitive dependencies
We achieved a clean, normalized schema that eliminates anomalies and improves consistency.

ACID Properties in DBMS

MATHAN S — Tue, 07 Oct 2025 09:58:42 +0000

Databases power almost every application we use daily—from banking systems to e-commerce platforms. To ensure data remains reliable, databases follow the ACID principles: Atomicity, Consistency, Isolation, and Durability.

In this blog, we’ll demonstrate ACID properties with SQL transactions using a simple Loan Management example.

Step 1: Setup the Schema

We’ll create a Loans table that stores customer loan detail

Enter the values to be inserted in the table

Check the result

ATOMICITY
All operations in a transaction must succeed or none should.

Update and roll back

Atomicity ensures no partial updates happen.

Consistency

Transactions must bring the database from one valid state to another. Invalid data should not enter the system.

Alter

Consistency ensures only valid data enters the database.

Isolation

Concurrent transactions should not affect each other’s intermediate results.

Isolation prevents dirty reads between transactions.

Durability

Once a transaction is committed, the changes must persist—even if the database crashes.

Durability guarantees committed data survives restarts.

Key Takeaways

Atomicity → All or nothing.
Consistency → Data always valid.
Isolation → Transactions don’t interfere.
Durability → Data persists after commit.
By applying ACID principles, databases remain reliable, fault-tolerant, and consistent even in high-concurrency environments like banking systems.

CRUD OPERATION

MATHAN S — Tue, 07 Oct 2025 08:42:20 +0000

MongoDB is one of the most popular NoSQL databases used by developers today for building modern, scalable applications. Unlike traditional relational databases, MongoDB stores data in flexible JSON-like documents, making it easier to work with real-world scenarios.

In this blog, We’ll walk through CRUD operations (Create, Read, Update, Delete) in MongoDB using a simple example: a student database. We’ll insert student details, query them, update academic information, and even delete records.

To make it more exciting, we’ll run these queries directly on MongoDB Atlas Cluster (cloud-based MongoDB). Along the way, I’ll include screenshots of my MongoDB Atlas dashboard and outputs so you can follow along visually.

Outcome:-

How to insert multiple documents into a collection

How to read and filter records using queries

How to update documents (single & multiple)

How to delete documents based on conditions

How CRUD fits into real-world development

Setup: Creating a Cluster

Create a free MongoDB Atlas account

Create a cluster and a database called collegeDB
Inside it, create a collection called STUDENTS

Create (Insert):-

Insert at least 5 student records into the students collection.

We cannot start by inserting 5 student records into our students collection together. We can create each student as separate document.

Code:-

{
student_id: "S001",
name: "harshitha",
age: 20,
department: "CSBS",
year: 2,
cgpa: 9
}

{
student_id: "S002",
name: "Madhumitha",
age: 21,
department: "CSBS",
year: 3,
cgpa: 8.5
}

{
student_id: "S003",
name: "Lokhitha",
age: 20,
department: "MI",
year: 3,
cgpa: 8
}

{
student_id: "S004",
name: "Harish",
age: 22,
department: "IT",
year: 3,
cgpa: 9.2
}

{
student_id: "S005",
name: "Dhaaraneesh",
age: 20,
department: "CIVIL",
year: 2,
cgpa: 8.8
}
{
student_id: "S006",
name: "Harish",
age: 22,
department: "CSE",
year: 3,
cgpa: 9.2
}

READ(QUERY)

Find all students with CGPA > 8.

db.students.find({ cgpa: { $gt: 8 } })

Find students belonging to the Computer Science department.

db.students.find({ department: "CSE" })

UPDATE

Update the CGPA of a specific student.

{ "student_id": "S005" }

Delete:-

Delete one student record by student_id.

{ "student_id": "S004" }

RESULT

Conclusion:-

In this blog, we explored how to perform CRUD operations in MongoDB using a real-world example of a student database. Starting from inserting records, querying based on conditions, updating multiple documents, and finally deleting specific records – we’ve covered the foundation of working with MongoDB.

Indexing, Hashing & Query Optimization in DBMS

MATHAN S — Sun, 05 Oct 2025 18:20:22 +0000

Definition:

Indexing: A database index is a data structure that enhances the speed of data retrieval operations on a table, though it comes with additional costs in terms of writes and storage space.

Hash Index: Utilizes a hash function to enable rapid equality searches. (Note: In Oracle, true hash indexes are not directly supported; hash-like performance can be achieved through specific functions or clustering techniques.)

B+ Tree Index: An extension of the B-Tree where all values are stored at the leaf nodes, making it more efficient for range queries.

B-Tree Index: A balanced tree-based index commonly used for equality and range queries.

STEPS:

Creating the Students Table

Inserting Sample Records

Creating a B-Tree Index on roll_no

SELECT * FROM Students WHERE roll_no = 110;

Creating a B+ Tree Index on cgpa

SELECT * FROM Students WHERE cgpa > 8.0;

Creating an Index on dept for Fast Equality Search

SELECT * FROM Students WHERE dept = 'CSBS';

DBMS – Transactions, Deadlocks & Log-Based Recovery

MATHAN S — Sun, 05 Oct 2025 18:04:53 +0000

Step 1: Create Table & Insert Data
CREATE TABLE CustomerAccounts ( acc_no INT PRIMARY KEY, name VARCHAR2(50), balance INT );
INSERT INTO CustomerAccounts VALUES (1, ‘EMILY, 1000); INSERT INTO CustomerAccounts VALUES (2, 'BOBBY, 1500); INSERT INTO CustomerAccounts VALUES (3, 'CALEB, 2000);
SELECT * FROM CustomerAccounts;

Transaction – Atomicity & Rollback

UPDATE CustomerAccounts SET balance = balance - 500 WHERE name = ‘Emily;

UPDATE CustomerAccounts SET balance = balance + 500 WHERE name = 'Bobby’;

Rollback transaction

SELECT * FROM CustomerAccounts;

DEADLOCK SIMULATION

-- Lock Emily UPDATE CustomerAccounts SET balance = balance - 100 WHERE name = ‘emily’; -- Do NOT commit
Session 2 (conceptual) -- Lock Bobby UPDATE CustomerAccounts SET balance = balance - 200 WHERE name = 'Bobby’; -- Do NOT commit
Continuing Session 1 -- Try updating Bobby (held by Session 2) UPDATE CustomerAccounts SET balance = balance + 100 WHERE name = 'Bobby’;
Continuing Session 2 -- Try updating Emily (held by Session 1) UPDATE CustomerAccounts SET balance = balance + 200 WHERE name = ‘Emily’;

LOG-BASED RECOVERY

Task: Show rollback and explain internal logs (undo/redo).
-- Update Charlie UPDATE CustomerAccounts SET balance = balance + 300 WHERE name = 'Charlie';
-- Rollback ROLLBACK;
-- Verify balances SELECT * FROM CustomerAccounts;

CURSOR AND TRIGGER

MATHAN S — Sun, 05 Oct 2025 17:37:48 +0000

CURSOR
A cursor in a Database Management System (DBMS) is a special control structure used to traverse and manipulate the rows in a result set one at a time. While standard SQL operations are typically set-based and act on all rows simultaneously, a cursor enables row-by-row processing, making it ideal for scenarios that require sequential logic, conditional operations, or custom computations on each individual row. Cursors are especially useful in complex business workflows where fine-grained control over data handling is necessary.

Step 1: Create Employee Table
CREATE TABLE Employee ( Emp_ID NUMBER PRIMARY KEY, Emp_Name VARCHAR2(50), Salary NUMBER );

Step 2: Insert Sample Data
INSERT INTO Employee (Emp_ID, Emp_Name, Salary) VALUES (1, 'Ramesh', 60000); INSERT INTO Employee (Emp_ID, Emp_Name, Salary) VALUES (2, 'Suresh', 45000); INSERT INTO Employee (Emp_ID, Emp_Name, Salary) VALUES (3, 'Anita', 75000); INSERT INTO Employee (Emp_ID, Emp_Name, Salary) VALUES (4, 'Kavya', 50000);

Step 3: Create and Process Cursor
OPEN emp_cursor; LOOP FETCH emp_cursor INTO v_EmpName, v_Salary; EXIT WHEN emp_cursor%NOTFOUND; DBMS_OUTPUT.PUT_LINE('Employee: ' || v_EmpName || ', Salary: ₹' || v_Salary); END LOOP; CLOSE emp_cursor; END;

DBMS_OUTPUT.PUT_LINE prints each employee’s name and salary.

DEFINITION OF TRIGGER IN DBMS

A trigger in DBMS is a special stored procedure that automatically executes in response to events like INSERT, UPDATE, or DELETE on a table or view. It’s commonly used to enforce business rules, maintain data integrity, and log changes without manual intervention.

Step 1: Create Students Table
CREATE TABLE Students ( Student_ID NUMBER PRIMARY KEY, Student_Name VARCHAR2(50), Course VARCHAR2(50) );

Step 2: Create Student_Audit Table
CREATE TABLE Student_Audit ( Audit_ID NUMBER GENERATED ALWAYS AS IDENTITY PRIMARY KEY, Student_ID NUMBER, Student_Name VARCHAR2(50), Action VARCHAR2(50), Action_Time TIMESTAMP );

Step 3: Create AFTER INSERT Trigger
CREATE OR REPLACE TRIGGER trg_after_student_insert AFTER INSERT ON Students FOR EACH ROW BEGIN INSERT INTO Student_Audit (Student_ID, Student_Name, Action, Action_Time) VALUES (:NEW.Student_ID, :NEW.Student_Name, 'INSERT', SYSTIMESTAMP); END;

Step 4: Test Trigger
INSERT INTO Students (Student_ID, Student_Name, Course) VALUES (1, 'Ravi', 'Computer Science'); INSERT INTO Students (Student_ID, Student_Name, Course) VALUES (2, 'Meena', 'Electrical Engineering');

Step 5: Verify Audit Table
SELECT * FROM Student_Audit;

COLLEGE STUDENT & COURSE MANAGEMENT SYSTEM

MATHAN S — Wed, 20 Aug 2025 16:15:50 +0000

Hey everyone! I'm just starting my journey into the world of tech, and this is my very first blog post on Dev.to. I'm diving into Database Management Systems (DBMS) — learning the basics, understanding how data is stored, and exploring why databases are so important in today’s digital world. This post is a beginner-friendly introduction, and I hope it helps others who are just starting out like me.

CREATING TABLE

To create a STUDENT table in DBMS, start by designing the table structure based on the information you want to store, such as student ID, name, date of birth, email, department. Once the design is ready, write the SQL CREATE TABLE statement

ALTERING TABLE

To add a phone number column to an existing STUDENT table in a database, you use the ALTER TABLE statement followed by the ADD keyword. This allows you to modify the structure of the table without deleting or recreating it. For example, the command ALTER TABLE STUDENT ADD phone VARCHAR(15);

SELECTING AND MAKING UPPERCASE

To retrieve a student's name in uppercase and calculate the length of their email address from the STUDENT table, you can use SQL functions in a SELECT query. The UPPER() function is used to convert the name to uppercase, and the LENGTH() (or LEN() in some databases) function is used to find the number of characters in the email. For example, the query SELECT UPPER(first_name) AS upper_name, LENGTH(email) AS email_length FROM STUDENT; will return the first name in all capital letters and the length of the email for each student.

DISPLAYING

To display the contents of the STUDENT table, you use the SELECT statement in SQL. The basic command SELECT * FROM STUDENT; retrieves all columns and all records from the table, showing the complete data stored for each student.