Introduction
SQL is a language for managing and querying relational databases, used in applications from web development to data analysis.
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Explore SQL Seeker for free SQL tutorials and resources. Perfect for beginners and intermediates aiming to master SQL coding skills.
SQL Basics
Syntax
SQL syntax is case-insensitive and uses semicolons to end statements, with variations across vendors like MySQL and PostgreSQL.
Read more →Data Types
SQL data types include INT, VARCHAR, and DATE, covering numeric and string data for structuring tables.
Read more →SELECT
SELECT retrieves data from tables using FROM, but avoid SELECT * to prevent performance issues.
Read more →WHERE
WHERE filters rows using conditions like AND, OR, and NOT for precise data retrieval.
Read more →ORDER BY
ORDER BY sorts results in ascending (ASC) or descending (DESC) order, supporting multiple columns.
Read more →DISTINCT
DISTINCT removes duplicate rows, with DISTINCT ON available in PostgreSQL for specific columns.
Read more →LIKE
LIKE enables pattern matching with wildcards, and ILIKE in PostgreSQL offers case-insensitive matching.
Read more →IN
IN filters data against multiple values, often paired with subqueries for dynamic filtering.
Read more →BETWEEN
BETWEEN filters data within inclusive ranges, ideal for numeric or date conditions.
Read more →NULL Handling
NULL handling uses IS NULL and IS NOT NULL, with COALESCE to manage default values.
Read more →LIMIT and OFFSET
LIMIT and OFFSET restrict result rows, with TOP as an alternative in SQL Server.
Read more →Aliases
Aliases with AS simplify column and table names, including implicit aliases for clarity.
Read more →Comments
SQL comments use -- for single-line or /* */ for multi-line annotations.
Read more →Case Sensitivity
SQL case sensitivity affects identifiers, with quoted identifiers enforcing exact matches.
Read more →Operators
SQL operators include arithmetic, comparison, and logical operators for building query conditions.
Read more →SQL Joins
INNER JOIN
INNER JOIN combines tables using the ON clause for matching rows.
Read more →LEFT JOIN
LEFT OUTER JOIN includes all rows from the left table, with NULLs for non-matching right table rows.
Read more →RIGHT JOIN
RIGHT OUTER JOIN includes all rows from the right table, with varying vendor support.
Read more →FULL JOIN
FULL OUTER JOIN combines all rows from both tables, handling NULLs for non-matches.
Read more →CROSS JOIN
CROSS JOIN creates a Cartesian product, useful for generating all possible combinations.
Read more →Self Join
Self JOIN connects a table to itself, often for hierarchical data like employee reporting structures.
Read more →SQL Aggregates
COUNT
COUNT tallies rows, with COUNT(*) including all rows regardless of NULLs.
Read more →SUM
SUM calculates the total of numeric values, ignoring NULLs.
Read more →AVG
AVG computes the mean of numeric values, handling NULLs automatically.
Read more →MIN and MAX
MIN and MAX find the smallest and largest values, applicable to strings and numbers.
Read more →GROUP BY
GROUP BY organizes rows into groups, often paired with HAVING for filtering.
Read more →HAVING
HAVING filters grouped data post-GROUP BY, refining aggregate results.
Read more →SQL Subqueries
Scalar Subqueries
Scalar subqueries return single values for use in SELECT or WHERE clauses.
Read more →Correlated Subqueries
Correlated subqueries with EXISTS check row dependencies, impacting performance.
Read more →IN Subqueries
IN subqueries filter data against multiple values, including NOT IN for exclusion.
Read more →ANY and ALL
ANY and ALL compare subquery results, with varying vendor support.
Read more →Data Manipulation
INSERT
INSERT INTO adds rows, supporting multi-row inserts for efficiency.
Read more →UPDATE
UPDATE modifies rows using SET, paired with WHERE for targeted changes.
Read more →DELETE
DELETE FROM removes rows, contrasted with TRUNCATE for full table clears.
Read more →MERGE
MERGE performs upserts, combining INSERT and UPDATE, with vendor-specific support.
Read more →INSERT INTO SELECT
INSERT INTO SELECT copies data from one table to another, supporting conditional transfers.
Read more →Schema Management
CREATE TABLE
CREATE TABLE defines tables with column constraints like PRIMARY KEY.
Read more →ALTER TABLE
ALTER TABLE adjusts table structures, supporting ADD and DROP operations.
Read more →DROP TABLE
DROP TABLE removes tables, with IF EXISTS to avoid errors.
Read more →Constraints
Constraints like PRIMARY KEY, FOREIGN KEY, and UNIQUE enforce data integrity.
Read more →Indexes
Indexes via CREATE INDEX boost query performance but increase storage.
Read more →Views
Views simplify queries, with materialized views for stored results.
Read more →CREATE DB
CREATE DATABASE initializes a new database, defining the storage environment.
Read more →DROP DB
DROP DATABASE deletes an entire database, with IF EXISTS for safety.
Read more →Default Constraints
DEFAULT constraints set default column values, simplifying data entry.
Read more →Auto Increment
Auto Increment generates sequential IDs, ideal for primary keys.
Read more →Stored Procedures
Stored procedures encapsulate SQL logic, improving modularity and performance.
Read more →SQL Functions
String Functions
String functions like CONCAT and SUBSTRING manipulate text, with 5–6 common options.
Read more →Numeric Functions
Numeric functions like ROUND and CEIL process numbers, including ABS and POWER.
Read more →Date Functions
Date functions like CURRENT_DATE and EXTRACT handle time, with vendor differences.
Read more →Conditional Functions
Conditional functions like CASE and COALESCE manage logic, including ORDER BY cases.
Read more →Type Conversion
Type conversion with CAST and CONVERT adjusts data types, varying by vendor.
Read more →JSON Functions
JSON functions like JSON_EXTRACT and JSON_ARRAY process JSON, supported in MySQL and PostgreSQL.
Read more →Advanced Queries
Window Functions
Window functions like ROW_NUMBER and RANK operate over partitions using OVER.
Read more →Common Table Expressions
Common Table Expressions with WITH simplify queries, supporting recursive CTEs.
Read more →Pivot Queries
Pivot queries use CASE or PIVOT to reshape data, with vendor-specific support.
Read more →Union Queries
UNION and UNION ALL combine results, with INTERSECT and EXCEPT for further operations.
Read more →Query Optimization
Query optimization uses EXPLAIN and indexes to improve performance via query plans.
Read more →SQL Security
Injection
SQL injection prevention relies on parameterized queries and prepared statements.
Read more →User Privileges
User privileges with GRANT and REVOKE control access, including role-based systems.
Read more →Data Sanitization
Data sanitization escapes inputs to ensure safe queries.
Read more →SQL Patterns
Filtering Data
Data filtering with WHERE, LIKE, and IN supports dynamic query patterns.
Read more →Sorting Data
Sorting with ORDER BY and CASE enables custom result ordering.
Read more →Grouping Data
Grouping with GROUP BY and HAVING, including ROLLUP, organizes data.
Read more →Joining Multiple Tables
Efficient multi-table joins consider join order for performance.
Read more →Paginating Results
Pagination with LIMIT and OFFSET balances performance and usability.
Read more →Hierarchical Queries
Hierarchical queries with CTEs or CONNECT BY (Oracle) manage tree-like data.
Read more →Dynamic Queries
Dynamic SQL queries use prepared statements for flexibility and safety.
Read more →Aggregate Reports
Aggregate reports use GROUP BY for summarized data insights.
Read more →Data Validation
Data validation with CHECK constraints and triggers ensures integrity.
Read more →SQL Examples
Simple Select
Basic SELECT query retrieves specific columns for targeted data access.
Read more →Filtered Query
Filtered query uses WHERE and LIKE with wildcards for precise results.
Read more →Sorted Query
Sorted query with ORDER BY supports multi-column sorting for ordered results.
Read more →Joined Query
Join query with INNER JOIN and ON clause combines two tables.
Read more →Aggregate Report
Aggregate report with COUNT and SUM uses GROUP BY for summaries.
Read more →Subquery Example
Scalar subquery in WHERE returns a single value for filtering.
Read more →Correlated Subquery
Correlated subquery with EXISTS checks row relationships, noting performance.
Read more →Insert Data
Inserting data with INSERT INTO supports default values for simplicity.
Read more →Update Data
Updating data with UPDATE and WHERE enables targeted row changes.
Read more →Delete Data
Deleting data with DELETE FROM supports cascading deletes for related rows.
Read more →Create Table
Creating a table with PRIMARY KEY constraints defines structured storage.
Read more →View Creation
Creating a view simplifies queries and supports limited updates.
Read more →String Manipulation
String manipulation with CONCAT and UPPER, including TRIM, processes text.
Read more →Date Calculations
Date calculations with date functions and INTERVAL compute time differences.
Read more →JSON Query
JSON query with JSON_EXTRACT processes JSON, leveraging PostgreSQL JSONB.
Read more →Window Function
Window function with ROW_NUMBER and PARTITION BY ranks rows.
Read more →CTE Example
Common Table Expression with CTE simplifies complex queries, including recursion.
Read more →Pivot Report
Pivot report with CASE statements or PIVOT (SQL Server) reshapes data.
Read more →Union Query
Union query with UNION ALL combines results, managing deduplication.
Read more →Paginated Query
Paginated query with LIMIT and OFFSET, noting OFFSET performance issues.
Read more →Hierarchy Query
Hierarchical query with CTE manages parent-child data relationships.
Read more →Sales Report
Sales report with aggregates and GROUP BY summarizes transaction data.
Read more →User Management
User management queries with CRUD and FOREIGN KEY handle user data.
Read more →Inventory Query
Inventory query with joins and aggregates tracks stock levels.
Read more →Search Query
Search query with LIKE and OR, including full-text search options.
Read more →Dynamic Filter
Dynamic filter query with CASE and prepared statements for flexibility.
Read more →Error Handling
Error handling with TRY-CATCH (SQL Server) manages query failures.
Read more →Data Export
Exporting data to CSV uses vendor tools for query results.
Read more →Data Import
Importing data with INSERT or LOAD DATA supports bulk operations.
Read more →Table Backup
Table backup with SELECT INTO or CREATE TABLE AS preserves data.
Read more →Query Logging
Query logging to audit tables supports auditing and monitoring.
Read more →Conditional Aggregation
Conditional aggregation with CASE in aggregates handles custom sums.
Read more →Cross Tabulation
Cross tabulation report with PIVOT or CASE creates summarized views.
Read more →Explore Our Tools
Cheat Sheet
Welcome to SQL Seeker's ultimate SQL Keyword and Cheat Sheet Reference!
Go to tool →Error Codes
SQL Seeker's SQL Error Code Lookup is your go-to reference for decoding common error codes in databases like MySQL and PostgreSQL.
Go to tool →Term Glossary
SQL Seeker's SQL Terminology Glossary is your quick reference for understanding essential SQL concepts.
Go to tool →JOIN Visualizer
Explore SQL JOINs with interactive visualizations and clear explanations to boost your database querying skills.
Go to tool →Query Explainer
This tool provides clear, plain-language explanations for your SQL queries to help you quickly understand and improve your SQL query comprehension.
Go to tool →Query Formatter
This tool allows you to easily format your raw SQL queries online, with support for various SQL dialects and customizable tab widths.
Go to tool →Query Translator
This tool converts your SQL statements between different database dialects helping you adapt queries for various systems.
Go to tool →Syntax Validator
This tool allows you to check and validate your SQL queries for correctness against a chosen dialect, enhancing code quality and reducing errors.
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