Convert Wiki to SQL

Why Convert Wiki to SQL?

Converting Wiki markup to SQL format enables you to extract tabular data from wiki pages and transform it into database-ready SQL statements. Wiki pages frequently contain valuable structured data in tables, including employee directories, product catalogs, configuration reference tables, and status tracking grids. By converting this data to SQL, you can import it directly into a relational database for querying, reporting, and integration with applications.

Wiki tables, while visually organized for human readers, are not machine-processable. The conversion analyzes wiki table structures, identifies column headers as field names, determines appropriate data types from the content, and generates CREATE TABLE and INSERT INTO statements. The result is a portable SQL script that can be executed against MySQL, PostgreSQL, SQLite, SQL Server, or any other standard relational database engine.

This conversion is particularly valuable for data migration projects where information has been manually maintained in wiki tables and needs to move into a proper database system. Rather than manually re-entering hundreds or thousands of table rows, converting the wiki source directly to SQL automates the process and reduces the risk of data entry errors. Section headings from the wiki become SQL comments, providing context and organization in the output script.

The generated SQL uses standard ANSI syntax for maximum portability across database platforms. Table and column names are derived from wiki table headers, values are properly quoted and escaped, and the output includes both schema creation (DDL) and data insertion (DML) statements. This complete approach means you can set up and populate a database table from a single SQL file generated from your wiki content.

Key Benefits of Converting Wiki to SQL:

• Data Extraction: Pull structured table data from wiki pages into databases
• Automated Migration: No manual data entry from wiki to database
• Schema Generation: CREATE TABLE statements derived from wiki headers
• Standard SQL: ANSI-compatible output works with any database engine
• Error Reduction: Eliminates manual transcription mistakes
• Bulk Import: Handle hundreds of wiki table rows in a single conversion
• Portable Output: SQL files import into MySQL, PostgreSQL, SQLite, and more

Practical Examples

Example 1: Product Catalog Wiki to Database

Input Wiki file (catalog.wiki):

== Product Catalog ==

{| class="wikitable"
|-
! SKU !! Product Name !! Price !! Category
|-
| WDG-001 || Standard Widget || 29.99 || Widgets
|-
| WDG-002 || Premium Widget || 49.99 || Widgets
|-
| GDG-001 || Basic Gadget || 19.99 || Gadgets
|-
| GDG-002 || Pro Gadget || 79.99 || Gadgets
|}

Output SQL file (catalog.sql):

-- Product Catalog
CREATE TABLE product_catalog (
    sku VARCHAR(20) PRIMARY KEY,
    product_name VARCHAR(255),
    price DECIMAL(10,2),
    category VARCHAR(100)
);

INSERT INTO product_catalog (sku, product_name, price, category) VALUES
    ('WDG-001', 'Standard Widget', 29.99, 'Widgets'),
    ('WDG-002', 'Premium Widget', 49.99, 'Widgets'),
    ('GDG-001', 'Basic Gadget', 19.99, 'Gadgets'),
    ('GDG-002', 'Pro Gadget', 79.99, 'Gadgets');

Example 2: Team Directory Wiki to Employee Table

Input Wiki file (team.wiki):

== Engineering Team ==

{| class="wikitable sortable"
|-
! Employee ID !! Name !! Role !! Start Date
|-
| E101 || Sarah Chen || Senior Developer || 2022-03-15
|-
| E102 || James Park || DevOps Engineer || 2023-01-10
|-
| E103 || Maria Garcia || QA Lead || 2021-08-22
|}

== Design Team ==

{| class="wikitable"
|-
! Employee ID !! Name !! Role !! Start Date
|-
| D201 || Tom Wilson || UX Designer || 2023-06-01
|-
| D202 || Lisa Brown || UI Designer || 2024-02-14
|}

Output SQL file (team.sql):

-- Engineering Team
CREATE TABLE engineering_team (
    employee_id VARCHAR(10) PRIMARY KEY,
    name VARCHAR(255),
    role VARCHAR(100),
    start_date DATE
);

INSERT INTO engineering_team VALUES
    ('E101', 'Sarah Chen', 'Senior Developer', '2022-03-15'),
    ('E102', 'James Park', 'DevOps Engineer', '2023-01-10'),
    ('E103', 'Maria Garcia', 'QA Lead', '2021-08-22');

-- Design Team
CREATE TABLE design_team (
    employee_id VARCHAR(10) PRIMARY KEY,
    name VARCHAR(255),
    role VARCHAR(100),
    start_date DATE
);

INSERT INTO design_team VALUES
    ('D201', 'Tom Wilson', 'UX Designer', '2023-06-01'),
    ('D202', 'Lisa Brown', 'UI Designer', '2024-02-14');

Example 3: Server Inventory Wiki to Asset Database

Input Wiki file (inventory.wiki):

== Server Inventory ==

{| class="wikitable"
|-
! Hostname !! IP Address !! OS !! RAM (GB) !! Status
|-
| web-prod-01 || 10.0.1.10 || Ubuntu 22.04 || 32 || Active
|-
| web-prod-02 || 10.0.1.11 || Ubuntu 22.04 || 32 || Active
|-
| db-prod-01 || 10.0.2.10 || RHEL 9 || 64 || Active
|-
| staging-01 || 10.0.3.10 || Ubuntu 22.04 || 16 || Maintenance
|}

Output SQL file (inventory.sql):

-- Server Inventory
CREATE TABLE server_inventory (
    hostname VARCHAR(100) PRIMARY KEY,
    ip_address VARCHAR(45),
    os VARCHAR(100),
    ram_gb INTEGER,
    status VARCHAR(50)
);

INSERT INTO server_inventory VALUES
    ('web-prod-01', '10.0.1.10', 'Ubuntu 22.04', 32, 'Active'),
    ('web-prod-02', '10.0.1.11', 'Ubuntu 22.04', 32, 'Active'),
    ('db-prod-01', '10.0.2.10', 'RHEL 9', 64, 'Active'),
    ('staging-01', '10.0.3.10', 'Ubuntu 22.04', 16, 'Maintenance');

Frequently Asked Questions (FAQ)

Q: What SQL dialect does the output use?

A: The converter generates standard ANSI SQL that is compatible with all major database engines including MySQL, PostgreSQL, SQLite, SQL Server, and Oracle. The syntax avoids vendor-specific extensions to ensure maximum portability. If you need dialect-specific features (like AUTO_INCREMENT for MySQL or SERIAL for PostgreSQL), you can adjust the output after conversion.

Q: How does the converter determine SQL data types?

A: The converter analyzes the content of each column to infer appropriate data types. Numeric values become INTEGER or DECIMAL, date-formatted strings become DATE, and text values use VARCHAR with appropriate length. When column content is mixed or ambiguous, VARCHAR is used as a safe default. You can adjust data types in the output to match your database schema requirements.

Q: Are wiki tables the only content converted to SQL?

A: Wiki tables are the primary content that maps to SQL INSERT statements since they contain structured tabular data. Non-table content such as headings become SQL comments (-- comment), and list items or paragraphs are included as comments to preserve context. The focus is on extracting machine-processable data from the structured wiki tables.

Q: Can I import the SQL output directly into MySQL?

A: Yes, you can execute the generated SQL file directly in MySQL using the command line (mysql -u user -p database < output.sql), MySQL Workbench, phpMyAdmin, or any MySQL client. The standard SQL syntax is fully compatible with MySQL. For very large datasets, you may want to add transaction wrappers for better import performance.

Q: How are special characters in wiki content handled?

A: String values in the SQL output are properly escaped to prevent syntax errors. Single quotes within text values are escaped as double single quotes (''), and wiki markup characters are stripped to produce clean data values. This ensures the generated SQL is syntactically valid and safe to execute against any database.

Q: What happens to wiki pages with multiple tables?

A: Each wiki table generates a separate CREATE TABLE and INSERT INTO block in the SQL output. Table names are derived from the nearest preceding heading or assigned sequential names (table_1, table_2) if no heading is available. This approach preserves the logical organization of the source wiki page in the database schema.

Q: Can I use this for migrating wiki data to a production database?

A: The generated SQL is suitable for development and staging environments. For production database migration, review the output to verify data types, add appropriate constraints (foreign keys, NOT NULL, unique), adjust table and column names to match your schema conventions, and test the import in a staging environment first. Always back up your production database before importing new data.

Q: Does the converter handle wiki markup within table cells?

A: Yes, wiki formatting within table cells (bold, italic, links) is stripped during conversion to produce clean text values for SQL insertion. The raw text content is preserved while markup syntax is removed. If formatted text within cells is important, consider converting to a format that supports rich text like HTML or DOCX instead of SQL.