Quick referenceSections

PostgreSQL

A relational database that keeps your data correct under pressure.

PostgreSQL is a relational database server: it stores data in typed tables, enforces the rules you declare on every write, and answers questions about that data through SQL. It is not merely a place SQL happens to run — every constraint you declare is checked on every write, which is what keeps the data trustworthy as more of it accumulates.

Difficulty
intermediate
Time
15+ hours
Sections written
22

Why it matters

  • It is the default system of record for data that must stay correct — orders, accounts, inventory — because it enforces constraints rather than trusting the application to.
  • MVCC lets readers and writers work concurrently without blocking each other for most workloads, which most other relational databases approximate less cleanly.
  • A single server can be the backbone for transactional data, JSON documents (JSONB), full-text search and analytics queries — before reaching for a specialized system.
  • Django and FastAPI both commonly sit on top of PostgreSQL, so the concepts here carry straight into two of the other topics here.

Where it is used

  • Systems of record — orders, accounts, inventory, anywhere correctness cannot be optional
  • Backends built on Django or FastAPI, both of which default to it
  • Multi-tenant SaaS, using schemas or row-level security for isolation
  • Analytics and reporting, via window functions, CTEs and materialized views

The big picture

How the pieces of PostgreSQL fit together
writes becomerow versionsMVCC makespossiblethe plannerreasons aboutis kepthealthy by

SQL

queries, joins, CTEs

Storage

MVCC, WAL, vacuum

Concurrency

locks, isolation, transactions

Performance

indexes, the planner

Operations

backup, replication, monitoring

  • SQL — queries, joins, CTEs
    • leads to Storage (writes become row versions)
  • Storage — MVCC, WAL, vacuum
    • leads to Concurrency (MVCC makes possible)
  • Concurrency — locks, isolation, transactions
    • leads to Performance (the planner reasons about)
  • Performance — indexes, the planner
    • leads to Operations (is kept healthy by)
  • Operations — backup, replication, monitoring

Sections

  1. PostgreSQL Fundamentalsbeginner24 min
  2. SQL Fundamentalsbeginner30 min
  3. Joinsintermediate32 min
  4. Subqueries and CTEsintermediate34 min
  5. Window Functionsintermediate30 min
  6. PostgreSQL Data Typesintermediate36 min
  7. NULL, Three-Valued Logic and Data Semanticsintermediate34 min
  8. Constraints and Data Integrityintermediate32 min
  9. Schema Design and Data Modelingintermediate38 min
  10. Primary Keys, Foreign Keys and Relationship Designintermediate34 min
  11. Viewsintermediate28 min
  12. Sequences and Identity Columnsintermediate26 min
  13. PostgreSQL Functions and Proceduresintermediate30 min
  14. Triggersintermediate30 min
  15. Transactions — Core Competencyintermediate34 min
  16. Isolation Levels and Concurrencyintermediate36 min
  17. MVCC — Must Understandintermediate32 min
  18. VACUUM, ANALYZE and Autovacuumintermediate34 min
  19. Storage and Table Internalsadvanced32 min
  20. Index Fundamentalsintermediate36 min
  21. B-Tree Indexesintermediate34 min
  22. Other Index Typesadvanced32 min
  23. Partial, Expression and Covering Indexes4 items
  24. Query Planning and EXPLAIN7 items
  25. PostgreSQL Query Planner6 items
  26. Query Optimization8 items
  27. Sorting, Aggregation and Hashing5 items
  28. Statistics5 items
  29. Common SQL Performance Problems13 items
  30. Pagination5 items
  31. JSON and JSONB6 items
  32. Arrays4 items
  33. Full-Text Search5 items
  34. Transactions in Real Applications5 items
  35. Locks6 items
  36. Advisory Locks4 items
  37. Upserts and Conflict Handling5 items
  38. Safe Counters and Atomic Updates4 items
  39. Date and Time6 items
  40. Numeric and Financial Data5 items
  41. PostgreSQL Security6 items
  42. Authentication and Connection Security6 items
  43. Row-Level Security5 items
  44. Schema and Search Path Security4 items
  45. Extensions3 items
  46. Connection Management5 items
  47. PostgreSQL Connection Pooling4 items
  48. Monitoring and Observability6 items
  49. Logging4 items
  50. Checkpoints and WAL5 items
  51. Crash Recovery4 items
  52. Backup and Restore6 items
  53. Point-in-Time Recovery5 items
  54. Replication6 items
  55. Logical Replication4 items
  56. High Availability6 items
  57. Partitioning5 items
  58. Sharding and Horizontal Scaling4 items
  59. Tablespaces and Storage Layout4 items
  60. Extensions and Specialized Workloads2 items
  61. Bulk Loading and COPY4 items
  62. Batch Updates and Deletes5 items
  63. Full-Text and Search Architecture3 items
  64. PostgreSQL with Python/Django7 items
  65. PostgreSQL with Async Backends4 items
  66. PostgreSQL Testing5 items
  67. Data Migrations5 items
  68. Operational Troubleshooting2 items
  69. Performance and Capacity Planning4 items
  70. PostgreSQL Anti-Patterns15 items
  71. Production Checklist14 items
  72. What a 5-Year PostgreSQL Engineer Should Be Able to Explain22 items
  73. Recommended Priority for a 5-Year PostgreSQL Engineer3 items
  74. Practical Projects to Validate PostgreSQL Skills5 items
  75. Recommended Learning Order1 item