Database Management System (DBMS) SQL Labs A comprehensive collection of hands-on SQL laboratories designed to teach database concepts from basic queries to advanced database management techniques. These labs provide practical experience with SQL, database design, and modern database technologies.
By completing these labs, students will:
Master fundamental SQL operations (SELECT, INSERT, UPDATE, DELETE)
Understand database design principles and normalization
Learn advanced SQL concepts (joins, subqueries, window functions)
Gain experience with database programming and interfaces
Explore modern database technologies (NoSQL, Graph databases)
Understand transaction management and concurrency control
Foundational Labs (SQL Basics)
Lab
Topic
Description
Resource
1
Database Creation & Basic Queries
Learn to create databases, tables, and perform simple SELECT operations
Lab 1
2
Advanced Queries & Joins
Master multi-table queries, joins, and complex WHERE clauses
Lab 2
3
Foreign Keys & Relationships
Understand referential integrity and table relationships
Foreign Keys
4
Multi-Table Operations
Practice complex joins and relationship queries
Multi Tables
Intermediate Labs (Advanced SQL)
Lab
Topic
Description
Resource
5
Set Operations & Nested Queries
Learn UNION, INTERSECT, and subquery techniques
Lab 2 Advanced
6
Aggregate Functions & Grouping
Master COUNT, SUM, AVG, GROUP BY, and HAVING clauses
Lab 2 Aggregates
7
Window Functions
Learn advanced analytical functions and partitioning
Window Functions
8
Views & Virtual Tables
Create and manage database views for data abstraction
Views Lab
Lab
Topic
Description
Resource
9
Database Normalization
Learn 1NF, 2NF, 3NF and database design principles
Normal Forms
10
Advanced SQL Techniques
Practice complex queries and optimization
Advanced SQL
Programming Integration Labs
Lab
Topic
Description
Resource
11
Python Database Interface
Connect Python applications to databases using connectors
Python Lab
12
Jupyter Notebook Integration
Interactive database analysis with Jupyter notebooks
Jupyter Lab
Advanced Database Concepts
Lab
Topic
Description
Resource
13
Analytical Functions
Master ROLLUP, CUBE, and advanced grouping operations
Rollup Lab
14
Triggers & Stored Procedures
Implement database automation and business logic
Triggers Lab
15
Transaction Management
Understand ACID properties and concurrency control
Transactions
16
Isolation Levels
Learn about database isolation and consistency
Isolation Levels
Modern Database Technologies
Lab
Topic
Description
Resource
17
JSON & XML Processing
Handle semi-structured data in relational databases
JSON/XML Lab
18
MongoDB (NoSQL)
Introduction to document-based databases
MongoDB Lab
19
Neo4j (Graph Database)
Explore graph database concepts and Cypher queries
Neo4j Lab
The repository includes several real-world datasets for hands-on practice:
Dataset
Description
Use Cases
IMDB Movie Data Movie information including ratings, genres, and revenue
Complex queries, aggregations, data analysis
Air Travel Data Flight and passenger information
Time-series analysis, grouping operations
Cities Data Geographic and demographic information
Joins, geographic queries
Employee Data HR database with employee information
Relationship modeling, hierarchical queries
Student Grades Academic performance data
Statistical analysis, ranking functions
Drivers Database Complete database schema with sample data
Full database operations, complex relationships
Beginners : Start with Labs 1-4 (Foundational Labs)Intermediate : Continue with Labs 5-8 (Advanced SQL)Advanced : Explore Labs 9+ (Database Design & Modern Technologies)
🛠️ Tools and Technologies
MySQL/MariaDB : Primary database system for most labsMongoDB : NoSQL document database (Lab 18)Neo4j : Graph database system (Lab 19)
SQL : Standard query language for relational databasesPython : Database connectivity and data analysisCypher : Query language for Neo4j graph database
Jupyter Notebooks : Interactive data analysis and visualizationCommand Line Tools : Direct database interactionDatabase Clients : GUI tools for database management
📖 Additional Learning Resources We welcome contributions to improve these labs! Please:
Fork the repository
Create a feature branch
Make your improvements
Submit a pull request
Additional practice exercises
New dataset examples
Improved explanations and documentation
Bug fixes and corrections
This project is licensed under the MIT License - see the LICENSE file for details.
Visit the project website at https://teachingow.github.io/DBMS-SQL-Labs/ for additional resources and updates.