Overview
Data is the foundation of every application. Master how to store, query, and scale it. From your first SQL query to designing globally distributed databases — every concept is taught hands-on with real engines.
🗺️ Choose Your Level
🌱 Foundations
Relational model, SQL basics, SELECT/JOIN/GROUP BY, schema design, ERDs. Set up MySQL and PostgreSQL from scratch.
⚙️ Practitioner
Advanced SQL, subqueries, window functions, indexing strategies, ACID transactions, and hands-on NoSQL with MongoDB and Redis.
📋 Curriculum Overview
Learn to think in tables, rows, and relationships
1–5
Relational model, installing MySQL/PostgreSQL, CREATE/INSERT/SELECT
6–10
WHERE, ORDER BY, GROUP BY, HAVING, aggregate functions
11–15
JOINs (INNER, LEFT, RIGHT, FULL), subqueries, views
16–20
Database design, normalisation (1NF–3NF), ERD, foreign keys, constraints
Databases: MySQL 8, PostgreSQL 15
Go beyond basics — write queries that perform
1–5
Window functions, CTEs, recursive queries, stored procedures
6–10
Indexing strategy, EXPLAIN ANALYSE, slow query log, covering indexes
11–15
ACID transactions, isolation levels, deadlocks, row locking
16–20
MongoDB CRUD, aggregation pipeline; Redis data structures, pub/sub, caching
Databases: MySQL, PostgreSQL, MongoDB, Redis
Build databases that survive failure and scale under load
1–5
MySQL/PostgreSQL replication (primary-replica), binary log
6–10
Horizontal sharding, partitioning, consistent hashing
11–15
Query profiling, buffer pool tuning, connection pooling (PgBouncer)
16–20
Encryption at rest/transit, audit logging, backup & point-in-time recovery
Tools: pgBouncer, ProxySQL, mysqldump, pg_dump, Percona
Design data systems at cloud and enterprise scale
1–5
Distributed databases, CAP theorem, eventual consistency, Paxos/Raft
6–10
AWS RDS (multi-AZ, read replicas), DynamoDB, Aurora Serverless
11–15
MongoDB Atlas, data warehousing (Redshift, BigQuery concepts)
16–20
Schema migrations at scale, zero-downtime deployments, data governance
Platforms: AWS RDS, DynamoDB, MongoDB Atlas, Snowflake concepts
⚡ Lab Format
Every lab uses a real database engine running in Docker with verified output:
Each lab includes:
🎯 Objective — clear goal and real-world relevance
🔬 8 numbered steps — progressive complexity, real SQL and shell commands
📸 Verified output — actual query results captured from live Docker runs
💡 Tip callouts — what each clause means and why it matters
🏁 Step 8 Capstone — a real-world scenario tying all concepts together
📋 Summary table — quick reference for the lab's key commands
🚀 Quick Start
🏆 Certifications Aligned
Oracle MySQL 8 Developer
Foundations + Practitioner
PostgreSQL Associate (EDB)
Foundations + Practitioner
MongoDB Certified Developer
Practitioner + Advanced
AWS Certified Database Specialty
Advanced + Architect
Google Professional Data Engineer
Architect
Snowflake SnowPro Core
Architect
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