A Free SQL Curriculum — 131 Chapters, From `SELECT` to Distributed Databases
Most SQL tutorials teach the same thing: SELECT , WHERE , JOIN , GROUP BY . Maybe window functions. Then they stop. The real questions come after that. Why is this query slow? What does the execution plan mean? How do transactions actually work? What is MVCC? I found a curriculum that answers those. It's on KandZ Tuts , and it's 131 chapters, organized as a single progression from relational…
A comprehensive free SQL curriculum is available on KandZ Tuts, consisting of 131 chapters that progress from the basics to distributed database internals. The curriculum covers everything from the fundamentals of relational databases to advanced features and database internals.
The first 13 chapters introduce the foundations, including what relational databases are, how an RDBMS enforces the model, tables and keys, DDL/DML/DCL/TCL/DQL categories, installing a database, data types, and various constraints. Chapters 14-28 focus on querying, covering SELECT and FROM, WHERE, comparison and logical operators, handling NULLs, ORDER BY, LIMIT/OFFSET/TOP, DISTINCT, INSERT, UPDATE, DELETE, and aliases.
Aggregation and joins are explored in chapters 29-42, with a discussion of aggregate functions, GROUP BY, HAVING, execution order, join types, and set operations. Subqueries and functions are covered in chapters 43-53, including subqueries in different clauses, correlated subqueries, EXISTS, ANY/SOME/ALL, CASE WHEN, COALESCE/NULLIF, and various string and date/time manipulations.
Chapters 54-65 delve into window functions and CTEs, including the OVER clause, partitioning, ranking and NTILE functions, leading and lagging values, window frame aggregation, ROWS vs RANGE frames, ROLLUP/CUBE/GROUPING SETS, CTEs and recursive CTEs for hierarchical data.
Chapters 66-81 cover transactions, indexes, and optimization, including views and materialized views, ACID properties, transaction control statements, isolation levels and concurrency issues, index types and maintenance, execution plans, normalization and denormalization.
Chapters 82-93 discuss procedural SQL and security, including user-defined functions, stored procedures, parameters, error handling, triggers, cursors, sequences, permissions, SQL injection prevention, row-level security, and data masking.
Advanced topics in chapters 94-100 include JSON handling, full-text search, table partitioning, locks and deadlocks, upsert patterns, sharding, read replicas, backup and restore strategies. Database internals are covered in chapters 101-113, including storage engines, write-ahead logging, buffer pool management, MVCC, lock escalation, optimizer statistics, join algorithms, query execution engines, specialized indexes, spatial data with PostGIS, temporal tables, graph queries, and columnar vs row storage.
The final chapters 114-125 focus on analytics and distributed systems, including data warehousing, Data Vault 2.0, slowly changing dimensions, MPP architecture, distributed SQL engines, two-phase commit, consensus protocols, XML and XPath, vector search with pgvector, change data capture, foreign data wrappers, dynamic SQL hazards, and database auditing.
Production concerns are addressed in chapters 126-131, covering compliance logging, cross-database migration, schema evolution, database unit testing, benchmarking, driver mechanics, and database auditing.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
