English | HTML | text-based course | 43 Lessons | 213 MB
A step-by-step journey to help you understand how PostgreSQL works from the inside out.
This course is designed for developers and anyone curious about what happens behind the scenes in PostgreSQL. You’ll start with simple SQL queries and gradually dive into how PostgreSQL works under the hood—covering the planner, transactions, B+ Trees, shared buffers, MVCC, WAL (Write-Ahead Logging), vacuum, and more.
Table of Contents
1 Why PostgreSQL Is More Than Just Data Storage
2 Inside PostgreSQL Unlocking Secrets with Trace Analysis
3 How a SQL Query Is Executed in PostgreSQL
4 PostgreSQL Architecture Inside the Database Engine
5 PostgreSQL Indexes Deep Dive for Developers
6 Why PostgreSQL Uses Heap Storage
7 How PostgreSQL Finds Rows in a B+ Tree_A Step-by-Step Example
8 B+ Tree Depth in PostgreSQL and Its Performance Impact
9 Index-Only Scans in PostgreSQL When Tables Are Skipped
10 Shared Buffers Explained What PostgreSQL Caches Internally
11 Understanding WAL in PostgreSQL The Write-Ahead Log
12 Inside PostgreSQL Writes From Shared Buffers to Disk
13 Why Doesn’t PostgreSQL Use Undo Logs for MVCC
14 MVCC Internals_How PostgreSQL Keeps Old Versions Alive
15 Autovacuum in PostgreSQL How It Works and When It Fails
16 PostgreSQL VACUUM Understanding Performance, Benefits, and Costs
17 System Catalogs The Metadata Control Center of a Database
18 Inside PostgreSQL How Transactions Really Work
19 PostgreSQL’s Hidden Strength Transactional DDL
20 How PostgreSQL Ensures Atomicity Using MVCC, CLOG, and WAL
21 Data Consistency in PostgreSQL_Constraints and Guarantees
22 Isolation Levels in PostgreSQL_A Practical Introduction
23 Same Isolation Level, Different Behavior PostgreSQL vs MySQL
24 Durability in PostgreSQL_How Crashes Don’t Lose Data
25 Why ROLLBACK Is So Fast in PostgreSQL
26 Checkpoints in PostgreSQL_What They Are and Why They Matter
27 Transaction ID Wraparound Why It Happens and How to Handle It
28 Locks in PostgreSQL_An Easy Guide to Types and Use Cases
29 Do Read-Only Queries Really Need VACUUM in PostgreSQL
30 Inside PostgreSQL’s Planner_From Query to Logical Plan
31 Inside PostgreSQL’s Cost Model How the Planner Thinks
32 How JOINs Work Internally in PostgreSQL
33 Join Tree Structures in Query Optimization
34 Join Enumeration Strategies Dynamic Programming vs Genetic Search
35 How PostgreSQL Reduces the Join Search Space
36 Understanding Join Graph Topology and Its Impact on Query Optimization
37 Why PostgreSQL Handles This JOIN 10× Faster Than MySQL
38 How PostgreSQL Aggregates Work Internally
39 PostgreSQL Parallel Query Execution The Key to Faster Analytics
40 WITH Queries Demystified How PostgreSQL Plans CTEs
41 How Databases Execute Window Functions A Deep Dive
42 Why PostgreSQL Query Optimization Is So Challenging
43 Planner Challenges in Distributed PostgreSQL
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