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SQL & Relational Database Engineering Complete Course
01.Introduction & Relational Database Architecture
02.Syntax, Clauses & Execution Order
03.SELECT: Column Projection & Expressions
04.SELECT DISTINCT & Row Deduplication
05.WHERE Clause: Filtering Predicates & Comparison
06.ORDER BY: Sorting, Multi-Column & NULLS Ordering
07.Logical Operators: AND, OR, NOT & Operator Precedence
08.Comments: Single-Line (--), Multi-Line (/* */) & Query Hints
09.Operators: Arithmetic, Bitwise & String Concatenation
10.LIKE Operator & Wildcard Characters (%, _)
11.IN & NOT IN: Membership Operators & Subqueries
12.BETWEEN: Range Filtering for Numbers, Dates & Text
13.NULL Values: Three-Valued Logic, IS NULL & IS NOT NULL
14.Aliases: AS Keyword for Columns & Tables
15.SELECT TOP, LIMIT & OFFSET Pagination
16.INSERT INTO: Single & Multi-Row Insertions
17.UPDATE: Modifying Existing Records & Safe WHERE Rules
18.DELETE: Removing Rows vs TRUNCATE TABLE
19.SELECT INTO & Table Backups (CREATE TABLE AS SELECT)
20.INSERT INTO SELECT: Bulk Data Migration
21.Aggregate Functions: Statistical Summaries
22.MIN() & MAX(): Finding Extremes Across Types
23.COUNT: COUNT(*), COUNT(column) & COUNT(DISTINCT)
24.SUM() & AVG(): Numerical Aggregation & Averages
25.GROUP BY: Aggregation Buckets & Categorical Metrics
26.HAVING: Filtering Aggregated Groups vs WHERE
27.Joins Architecture: Relational Modeling & Venn Diagrams
28.INNER JOIN: Matching Intersections Across Tables
29.LEFT JOIN: Preserving Unmatched Left Rows & Finding Orphans
30.RIGHT JOIN: Preserving Unmatched Right Rows
31.FULL JOIN: Full Outer Join & Complete Reconciliation
32.SELF JOIN: Hierarchies, Trees & Parent-Child Relationships
33.UNION: Combining Result Sets with Automatic Deduplication
34.UNION ALL vs UNION: Performance & Duplicates
35.EXISTS & NOT EXISTS: Correlated Subqueries
36.ANY & ALL: Quantified Comparison Subqueries
37.CASE: Conditional Expressions & Data Transposition
38.Null Functions: COALESCE, IFNULL, ISNULL & NULLIF
39.Stored Procedures, Functions & Query Parameters
40.CREATE & DROP DATABASE: Environment Lifecycle
41.CREATE TABLE: Defining Schemas & Types
42.DROP & TRUNCATE TABLE: Structure vs Data Purging
43.ALTER TABLE: Modifying Columns & Schema Evolution
44.AUTO INCREMENT & Sequences: Identity Generation
45.Date & Time Formats: Timestamp Manipulation
46.Views: Virtual Tables & Security Layers
47.Constraints Overview: Relational Integrity
48.NOT NULL & UNIQUE: Data Invariants
49.PRIMARY KEY: Entity Uniqueness & Clustering
50.FOREIGN KEY: Referential Integrity & Cascades
51.CHECK & DEFAULT: Business Rules at DB Layer
52.CREATE INDEX: B-Trees & Query Optimization
53.Injection Defense: Threat Models & Prevention
54.Parameters & Prepared Statements: Safe Execution
55.Database Engines & Hosting Architecture
56.Dialect References & Data Type Standards
57.Production Best Practices & Query Tuning Checklist
58.Interactive Exercises: Multi-Table Analytics Challenges
59.Comprehensive Assessment & Knowledge Check
60.Capstone Project: Enterprise Analytics Engine
61.Mastery Certification & Graduate Verification
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LearnSQL LIKE Operator & Wildcard Characters (%, _)
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Lesson 10 of 61
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SQL LIKE Operator & Wildcard Characters (%, _)

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In Plain English

The `LIKE` operator performs pattern matching on string columns. It uses two universal wildcard characters: `%` (matches zero, one, or multiple characters) and `_` (matches exactly one single character).

The Mental Model

"`%` is like an accordion that stretches to fit any number of letters; `_` is a single fixed empty blank tile waiting for exactly one letter."

Deep Dive: How It Works

Wildcard Patterns: `'a%'` (starts with "a"), `'%a'` (ends with "a"), `'%or%'` (contains "or"), `'_r%'` (has "r" in second position), `'a_%_'` (starts with "a" and is at least 3 characters long).

Case Sensitivity: Standard SQL LIKE is case-sensitive; PostgreSQL provides `ILIKE` for case-insensitive matching; SQLite LIKE is case-insensitive for ASCII by default.

Escaping Wildcards: If searching for literal `%` or `_`, use an escape clause: `WHERE discount LIKE '50\%' ESCAPE '\'`.

Syntax Blueprint

SELECT column1
FROM table_name
WHERE column1 LIKE 'Zen%';    -- Starts with Zen

Use % for arbitrary length text matching and _ for exact single character positions.

PointCore Rules to Remember

Point star
Prefix Matching Performance: `LIKE 'prefix%'` can use B-Tree indexes efficiently; leading wildcards `LIKE '%suffix'` force full table scans.
Point star
NOT LIKE: Inverts the match to exclude specific patterns: `WHERE email NOT LIKE '%.test'`.
Point star
Single Character _: `WHERE code LIKE 'A_C'` matches ABC, A1C, but not ABBC.

Common Beginner Traps & How to Fix Them

Mistake:Using `LIKE '%query%'` everywhere and wondering why queries become slow on 10M rows.

Why it happens: Leading `%` prevents the database from using standard B-Tree index ordering.

How to fix: Use full-text search engines (FTS / PostgreSQL tsvector) or prefix matching when possible.

Pro Tip: In PostgreSQL, use `ILIKE` for case-insensitive pattern matching; in MySQL, use `LIKE BINARY` to enforce strict case sensitivity.

Live Interactive Example

Hit Run Code to see it live
Filtering Email Domains and Product Codes with LIKE
Python 3.12
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Output Console
Click "Run Code" to view the rendered output.
How it works: % matched arbitrary domain prefixes, and ___ matched exactly 3 trailing characters.

Your Turn: Micro Challenge

No pressure! Edit the starter code below and test your solution with instant feedback.

Micro Exercise

Filter Names Starting with "J"

  • PointSelect `name` from `contacts` where `name LIKE 'J%'`.
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Sandbox Output
Click "Run & Check" to test your solution.

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