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Table and Field Configuration ​

This guide details how to configure table-level metadata, column definitions, data types, business constraints, and advanced field features to generate reliable DDL.

Overview ​

Use the visual editor to design greenfield database tables or evolve existing schemas while guaranteeing conformance to your chosen database dialect's syntax and type rules.

Configuration Walkthrough ​

1. Table-Level Metadata ​

Configure table identifiers in the top configuration header:

  • Database Type: Select your target database dialect (e.g., MySQL, PostgreSQL, Oracle, SQL Server).
  • Table Name & Display Name: Enter the physical table name (e.g., order_item) and descriptive business label (e.g., Order Item Details).
  • Schema Name (Optional): If your database uses namespace isolation (e.g., sales.order_item), enter the schema name in the dedicated input. Do not manually prefix the table name.

2. Columns and Constraints ​

Define column properties in the Field Configuration table:

  • Field Name & Label: Specify the column identifier and its business description.
  • Data Type: Select from dialect-aware data types (such as BIGINT, VARCHAR(255), DECIMAL(10,2), JSON).
  • Nullability: Explicitly mark columns as NOT NULL or NULL.
  • Default Type & Default Value: Choose from constant values, empty strings, current timestamp (CURRENT_TIMESTAMP), UUIDs, or dialect-specific expressions.
  • Update Policy: Configure automatic update triggers for timestamp columns (e.g., ON UPDATE CURRENT_TIMESTAMP).

3. Productivity & Layout Features ​

  • Batch Row Insertion & Reordering: Click "Add Rows" to quickly insert multiple column rows. Drag rows by their left handles to reorder columns in the DDL.
  • Frozen Columns & Compact Layout: Pin key identifier columns with "Freeze Columns" when scrolling horizontally. Toggle "Compact Layout" on smaller displays to maximize visible information density.
  • Field Templates: Click "Apply Template" to insert standard audit column bundles (e.g., created_at, updated_at, created_by), or save current columns as a reusable team template.

4. Advanced Metadata & Tools ​

  • Logical Enums: For finite status columns, expand the inline enum editor to specify valid values, labels, and visual color badges. This metadata persists with the table to document business rules.
  • Storage Capacity Estimation: Click "Estimate Storage" and input projected row counts. The tool computes physical disk usage including row width and index overhead.
  • Schema Lint: Run the built-in Schema Lint checker to catch naming convention violations, problematic data types, or missing primary keys.
  • Mock Data Generator: Click "Mock Data" to generate realistic sample datasets based on column types, exportable as SQL INSERT statements, CSV, or JSON.

Verification Checklist ​

  • [ ] All core domain fields are accurately defined with appropriate types and lengths.
  • [ ] Primary key and non-null constraints are correctly applied.
  • [ ] The DDL output panel updates in real time with syntactically valid SQL.
  • [ ] The Schema Lint panel reports no critical errors.

Common Traps and Guidance ​

Column Type Migrations

Modifying data types on established tables may trigger compatibility warnings (such as truncation or precision loss). Carefully inspect warnings before applying changes.

  • Reserved Keywords: When a column name matches a database reserved word (e.g., order, status, group), the system displays a warning and automatically quotes the identifier in generated DDL.
  • Foreign Key Requirements: When configuring foreign keys or drawing relationship lines in the ER diagram, target columns must be single-column primary keys or unique index targets with matching data types.