The First Database

IBM (International Business Machines) is a multinational technology company founded in 1911 by Charles Ranlett Flint. IBM created the world’s first major database system, IMS (Information Management System), in 1966, which is a hierarchical database organizing data in a tree-like structure with parent-child relationships. Later, IBM developed DB2, a popular SQL-based relational database. The company is a pioneer in databases, mainframes, and enterprise software and is widely known as “Big Blue.”
  • What is a Database?

A database is an organized collection of data that allows users to store, retrieve, update, and delete information easily.

  • Why Databases are Important?

Databases are essential for modern applications because they:

  • Store large amounts of data efficiently.
  • Provide fast access and retrieval for applications.
  • Ensure data consistency and integrity across transactions.
  • Provide security and access control to protect sensitive information.
  • Support multiple concurrent users without conflicts.
  • Enable backup and recovery to prevent data loss.
  • Offer scalability to handle increasing workloads.
  • Allow analytics and reporting to make informed decisions.
  • Facilitate real-time data processing for dynamic applications.
  • Types of Databases

Type

Description

Examples

Relational

 Data stored in structured tables with rows and columns

MySQL, PostgreSQL, Oracle, SQL Server

Non-Relational

 Flexible, schema-less data storage MongoDB, Redis, CouchDB

Centralizedq

 Stored at a single location

Bank systems

Distributed

 Stored across multiple locations Cassandra, CockroachDB, Amazon DynamoDB

Cloud / Managed

 Fully managed databases hosted in the cloud Amazon RDS, Google Cloud SQL, Azure SQL Database
  • SQL (Structured Query Language)

SQL is a standard language used to communicate with relational databases. SQL (Structured Query Language) was created by Donald D. Chamberlin and Raymond F. Boyce at IBM in the early 1970s while working on the System R relational database project. It was originally called SEQUEL (Structured English Query Language) before being renamed SQL.

SQL databases use fixed schemas – structure must be defined before adding data.

  • Common SQL Commands

Category

Full Form

Purpose

Commands
DDL Data Definition Language Defines database structure CREATE, ALTER, DROP, TRUNCATE, RENAME
DML Data Manipulation Language Manipulates table data INSERT, UPDATE, DELETE
DQL Data Query Language Retrieves data SELECT
DCL Data Control Language Controls access & permissions GRANT, REVOKE
TCL Transaction Control Language Manages transactions COMMIT, ROLLBACK, SAVEPOINT
  • DDL Examples 
CREATE TABLE students (id INT PRIMARY KEY, name VARCHAR(50), age INT);
ALTER TABLE students ADD email VARCHAR(100);
RENAME TABLE students TO student_details;
TRUNCATE TABLE student_details;
DROP TABLE student_details;
  • DML Examples 
INSERT INTO students VALUES (1, 'Rahul', 21);
UPDATE students SET age = 22 WHERE id = 1;
DELETE FROM students WHERE id = 1;
  • DQL Examples 
SELECT * FROM students;
SELECT name, age FROM students WHERE age > 18;
  • DCL Examples 
GRANT SELECT, INSERT ON students TO user1;
REVOKE INSERT ON students FROM user1;
  • TCL Examples 
COMMIT;
ROLLBACK;
SAVEPOINT sp1;
ROLLBACK TO sp1;
  • NoSQL (Not Only SQL)

NoSQL (Not Only SQL) databases, first created by Carlo Strozzi in 1998, handle unstructured or rapidly changing data without fixed schemas. Unlike SQL databases, which use fixed schemas defining tables, fields, and relationships, NoSQL databases often have flexible or schema-less designs, allowing dynamic data. They use key-value, document, column, or graph formats, are highly scalable, and ideal for big data and real-time applications. Popular examples include MongoDB, Cassandra, Redis, and Neo4j.

NoSQL databases often use flexible or schema-less designs, allowing dynamic or unstructured data.

  • MongoDB (Document Database) Examples 
db.users.insertOne({ name: 'Rahul', age: 41, city: 'Delhi' });
db.users.find({ age: { $gt: 18 } });
db.users.updateOne({ name: 'Rahul' }, { $set: { age: 22 } });
db.users.deleteOne({ name: 'Rahul' });
  • Redis (Key-Value Database) 
SET username "rahul"
GET username
DEL username
  • Cassandra (Column Database) 
CREATE (u:User {name: 'Rahul'});
MATCH (u:User {name:'Rahul'}) CREATE (u)-[:FRIEND_OF]->(:User {name:'Amit'});
MATCH (u:User)-[:FRIEND_OF]->(f) RETURN f.name;
  • SQL vs NoSQL – Comparison Table
Feature SQL NoSQL
Database Type Relational (RDBMS) Non-Relational
Data Structure Tables (rows & columns) JSON, key-value, graph, column
Schema Fixed schema Dynamic schema
Query Language SQL Database-specific
Scalability Vertical (scale up) Horizontal (scale out)
Relationships Strong (joins) Weak / embedded
Transactions ACID compliant

BASE (eventual consistency)
Performance Best for complex queries Best for large-scale, fast data
Flexibility Low High
Examples MySQL, Oracle MongoDB, Redis
  • ACID vs BASE

ACID (Used in SQL Databases) : 

Letter

Full Form

Meaning
A Atomicity All-or-nothing transactions
C Consistency Data remains valid before & after transaction

I

 Isolation Transactions do not interfere with each other

D

 Durability Committed data is permanent

BASE (Used in NoSQL Databases)

Letter

Full Form

Meaning

BA

 Basically Available The system always responds, even if some nodes fail.
S Soft State The system’s state may change over time, even without input.
E Eventual Consistency Data becomes consistent eventually across all nodes.
  • When to Use SQL or NoSQL

SQL Use Cases

Scenario Example
Banking systems MySQL/PostgreSQL for transactions
E-commerce orders PostgreSQL for payments and orders
College management Student-Course databases
Inventory management Product, supplier, stock tables 
SELECT o.order_id, c.name FROM orders o JOIN customers c ON o.customer_id = c.id;

NoSQL Use Cases

Scenario

Example
Social media apps MongoDB for user posts
Real-time chat Firebase for messages
IoT & logs Cassandra for sensor data
Caching Redis for session storage 
{ "user": "rahul", "message": "Hello world", "time": "10:30 PM" }

Hybrid SQL + NoSQL

Use Case SQL Role NoSQL Role
E-commerce app Orders & payments Product search & caching
Social platforms User accounts Posts, feeds, likes
Analytics systems Master data Logs & real-time data
  • Popular Databases & Query Technologies

SQL Databases

Database Use Case
MySQL Web apps
PostgreSQL Analytics, enterprise apps
Oracle Large enterprise systems
SQL Server Microsoft ecosystem

NoSQL Databases

Database

 Type

Use Case
MongoDB Document Flexible JSON data
Redis Key-Value Caching, sessions
Cassandra Column Big data, IoT
Neo4j Graph Relationship-heavy data

FAQ – Frequently Asked Questions

01. What is the difference between SQL and NoSQL?

SQL databases are relational and use structured tables, while NoSQL databases are non-relational and use flexible models like JSON or key-value.

No, SQL is a language used to communicate with databases like MySQL or PostgreSQL.

Neither is universally better. SQL is ideal for structured data and strong consistency, NoSQL is ideal for scalability and flexibility.

Yes, many modern applications use both to optimize performance.

No, they coexist and are used depending on application requirements.

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