🌟 PostgreSQL Uncovered: Internals, Trace Analysis, and Performance

A step-by-step journey to help you understand how PostgreSQL works from the inside out.

🎓 About the Course

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.

You'll learn not just what PostgreSQL does — but why it does it that way.

• 🧩 Total Lessons: 60
• 📅 Release Schedule: Starting October 1, we plan to publish five new lessons each week.
• 📌 The full course will be available by January 1, 2026.

🚀 Extra Benefits

This is the standard package for the full learning experience:

💬 Private Discord Community
Join a members-only space where you can ask questions and share insights.

📨 Discord Access
After purchasing the course, you’ll receive a Discord invite by email (usually within 3 days). Please check your inbox carefully.
If you haven’t received it, contact wangbin579@gmail.com.

🔍 PostgreSQL Trace Tool
Get access to a high-performance tracing program built on a specific PostgreSQL version. Use it to explore how SQL statements are parsed, optimized, and executed in real time.

📌 Note: The download link for the trace tool is available in the Discord #trace-help channel.

📚 Course Outline

PostgreSQL Uncovered: Internals, Trace Analysis, and Performance

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 Traverses B+ Trees to Locate Rows

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 Cache 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. PostgreSQL Isolation Levels: A Practical Guide

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. PostgreSQL Locks: A Simple Guide to Types and Use Cases

29. Do Read-Only Queries Really Need VACUUM in PostgreSQL?

30. Inside PostgreSQL’s Planner_From Query to Plan

31. How JOINs Work Internally in PostgreSQL

32. WITH Queries Demystified: How PostgreSQL Executes CTEs

33. How Databases Execute Window Functions: A Deep Dive

34. Mastering Join Optimization in PostgreSQL

35. PostgreSQL Parallel Query Execution: The Key to Faster Analytics

36. Why PostgreSQL Sometimes Fails to Reuse Execution Plans

37. Inside PostgreSQL’s Query Planner: Why Optimization Is So Hard

38. INSERT Internals: What Happens Under the Hood

39. UPDATE Internals: Versioning, WAL, and Visibility

40. Hotspot Row Updates: Why They Hurt PostgreSQL Performance

41. DELETE Execution Flow in PostgreSQL

42. Temporary Files in PostgreSQL: When and Why They're Used

43. Large Transactions: The Hidden Costs and Recovery Delays

44. Why Long Transactions Are Dangerous in PostgreSQL

45. Why Simple Queries May Still Run Slowly

46. What Causes Query Jitter in PostgreSQL?

47. Choosing Primary Keys: A Critical Choice for Performance and Design

48. Pagination Optimization: Avoiding Performance Hits from Large Offsets

49. Partitioning in PostgreSQL: Techniques, Benefits, and Pitfalls

50. What PostgreSQL Extensions Are and How They Work

51. Top PostgreSQL Extensions & Where They Shine

52. Understanding Hstore’s Extension Mechanism in PostgreSQL

53. Inside PostgreSQL Extensions: How FDW Works Under the Hood

54. MySQL vs PostgreSQL: Comparative Suitability for Distributed Architectures

55. Trace Analysis Case 1: Why Hot Updates to a Single Row Can Severely Impact Its Read Performance

56. Trace Analysis Case 2: Why Partitioning Performance Can Be So Poor

57. Trace Analysis Case 3: Why Long-Term TPC-C Tests Exhibit Significant Performance Fluctuations

58. Migrating from MySQL to PostgreSQL: Key Differences You Need to Know

59. PostgreSQL Production Survival Guide: What Every Team Must Know

60. Becoming a PostgreSQL Expert: Roadmap to Rapid Growth

📌 Important Notes

🗓️ Course publication schedule: Publish up to Course 29 by October 31, up to Course 45 by November 30, and complete all courses by December 31.

💬 If you’re unsure about purchasing the course, feel free to join our Discord community(https://discord.gg/g8ksTXPPnY) to ask questions and review the first few lessons.

⚠️ Please note: This is a digital product with instant access upon purchase.
All sales are final and non-refundable.