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system Advanced 21 lessons

Database Internals

Understand how databases work under the hood. Master B-Trees, Write-Ahead Logging (WAL), locking, and query execution engines.

Don't just use databases; understand them. This course dives into the internal architecture of relational database systems (like PostgreSQL/MySQL). You will learn how storage engines organize data on disk using Pages and B-Trees. Master the ACID properties through Write-Ahead Logging (WAL) and Concurrency Control (Locking/MVCC). We explore how the Query Optimizer parses SQL and selects execution plans. Essential for engineers optimizing high-load systems.

100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
DB Engineers
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Complete Course Syllabus

  • 1
    Storage Engines
    How data is persisted to disk pages and files.
  • 2
    Indexing Internals
    Implementing B-Trees and LSM Trees structures.
  • 3
    Transactions & ACID
    Write-Ahead Logs (WAL) and crash recovery.
  • 4
    Concurrency Control
    Locking, latches, and Isolation Levels (MVCC).
  • 5
    Query Execution
    Parsing, planning, and executing SQL commands.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$130k - $180k

Career Paths

Database Engineer $140k-$190k
Systems Architect $150k-$200k
Performance Eng $130k-$180k

What You Will Learn

Explain database storage structures like B-Trees and Heaps
Understand Transaction management and ACID properties internals
Analyze Query Execution lifecycles from parsing to fetching
Implement basic storage engines and indexing algorithms
Optimize queries based on internal database mechanics

Skills You Will Gain

Database Architecture C++ Data Structures Concurrency Control Query Optimization

Who Is This For

Backend Engineers
DBAs
Systems Programmers

Prerequisites

Systems Programming
Data Structures

Database Internals FAQs

Build one?

Yes, we build a simple clone to learn.

Which DB?

Concepts apply broadly; we use Postgres as reference.

C++ needed?

Yes, most database kernels are written in C/C++.

Practical?

Helps you debug complex production performance issues.

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