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SQL to TypeScript Interface Generator

Convert SQL DDL CREATE TABLE statements into strict, production-ready TypeScript interfaces and types with custom naming and nullability controls.

SQL DDL Input

Quick Schemas:

Target SQL Dialect

Property Casing

CREATE TABLE Statements2 tables detected

Client-Side Processing (0 Server Calls)15 Columns Total

TypeScript Definitions

Declaration Syntax

Nullable Handling

Interface Prefix

Interface Suffix

export keywordInline commentsreadonly PKsJSON as Record

export interface Users {
  id: string; // Primary Key | raw: UUID
  email: string; // raw: VARCHAR(255)
  full_name: string; // raw: TEXT
  is_active: boolean; // raw: BOOLEAN
  metadata: Record<string, unknown> | null; // raw: JSONB
  created_at: string; // raw: TIMESTAMPTZ
  deleted_at: string | null; // raw: TIMESTAMPTZ
}

export interface Orders {
  id: number; // Primary Key | raw: BIGSERIAL
  user_id: string; // raw: UUID
  order_number: string; // raw: VARCHAR(64)
  subtotal: number; // raw: NUMERIC(12, 2)
  tax_amount: number; // raw: NUMERIC(10, 2)
  status: string; // raw: VARCHAR(32)
  shipped_at: string | null; // raw: TIMESTAMP
  created_at: string | null; // raw: TIMESTAMP
}

Strict TypeScript 5.x Ready

Architectural Foundations: Bridging Relational Schemas and Strict TypeScript

Modern enterprise applications depend on rigid type safety spanning the entire data lifecycle: from the relational storage layer managed by PostgreSQL, MySQL, or SQLite up to the server runtime in Node.js, Bun, or Next.js edge functions. Manually transcribing SQL Data Definition Language (DDL) schemas into TypeScript types is error-prone, leading to type drift, unhandled null references, and silent production crashes.

Dialect Type Harmonization

Relational engines vary widely in numeric representations. PostgreSQL uses SERIAL and NUMERIC(10,2), MySQL uses TINYINT(1) and BIGINT UNSIGNED, while SQLite collapses types into dynamic affinities. Converting these reliably prevents runtime parsing mismatches.

Null Safety Compliance

SQL columns default to nullable unless explicitly annotated with NOT NULL or PRIMARY KEY. Generating strict union types such as string | null enforces proper compiler checks before accessing nested fields.

Client-Side Confidentiality

Database schemas contain sensitive structural metadata, compliance columns, and internal business logic. TwisterTools executes all AST tokenization and code generation directly inside your web browser without dispatching data across external APIs.

SQL Engine to TypeScript Type Mapping Specification

The table below documents how foundational SQL column primitives across major relational database engines are compiled into strict TypeScript interfaces:

SQL Data Category	PostgreSQL Primitives	MySQL / MariaDB Primitives	SQLite 3 Primitives	TypeScript Output
Numerics & Auto-IDs	INT, SERIAL, BIGINT, NUMERIC	INT, BIGINT, DECIMAL, FLOAT	INTEGER, REAL	number
Strings & Identifiers	VARCHAR, TEXT, UUID, CITEXT	VARCHAR, TEXT, CHAR, ENUM	TEXT	string
Booleans & Flags	BOOLEAN, BOOL	TINYINT(1), BIT, BOOL	INTEGER (0 or 1)	boolean
Timestamps & Dates	TIMESTAMPTZ, DATE, TIME	DATETIME, TIMESTAMP, DATE	TEXT, REAL	string
Structured Documents	JSON, JSONB	JSON	TEXT (JSON)	Record<string, unknown>
Raw Binary & Blobs	BYTEA	BLOB, LONGBLOB, BINARY	BLOB	Uint8Array

Best Practices for Managing Database Types in Production

Integrating generated TypeScript interfaces into Next.js, Express, Fastify, or Kysely projects requires deliberate structural patterns to maximize maintainability:

Interface vs Type Alias Recommendations

• Use Interfaces for Data Rows: Interfaces compile faster in TypeScript compiler daemon caches and support declaration merging when augmenting database models with computed relations.
• Use Type Aliases for Mutation Payloads: Combine utility helpers like Omit<User, 'id' | 'createdAt'> to create clean insert/update contracts without duplicate definitions.
• Flag Readonly Primary Keys: Mark IDs as readonly to prevent accidental mutations in domain service layers.

Automated Workflow Integration

• Centralize Types in a Shared Package: Store generated output under types/database.ts or an internal npm monorepo package shared between backend microservices and frontend clients.
• Preserve ORM Neutrality: Unlike Prisma or TypeORM entities that couple schema to heavy runtime decorators, raw TypeScript interfaces remain compatible with Prisma, Drizzle, Kysely, Knex, and pg-promise.
• Consistent Null Semantics: Standardize on explicit | null rather than optional ? to reflect true SQL NULL semantics. If your application parses incoming HTTP responses rather than raw database tables, use our JSON to TypeScript Interface Generator to infer strict interfaces directly from runtime API response bodies.

Frequently Asked Questions (FAQ)

How are SQL NULL and NOT NULL constraints handled in TypeScript?

By default, columns without an explicit NOT NULL clause or PRIMARY KEY definition are treated as nullable. The generator lets you configure whether these compile into explicit union types (field: string | null), optional properties (field?: string), or both combined to match your application convention.

Which SQL dialects are supported by this converter?

The parser supports PostgreSQL, MySQL, MariaDB, SQLite, and Microsoft SQL Server (T-SQL). It accurately parses dialect-specific syntax such as AUTO_INCREMENT, SERIAL, IDENTITY(1,1), JSONB, CITEXT, ENUM arrays, and table-level PRIMARY KEY constraint blocks.

Can I enforce camelCase property naming from snake_case database tables?

Yes. Use the Property Casing dropdown to automatically convert database column names to camelCase, snake_case, PascalCase, or keep original identifiers unchanged. Reserved words and special characters are safely escaped.

Is my proprietary SQL schema uploaded or stored on any server?

No. The tool runs 100% in your local browser runtime via client-side JavaScript. Neither your database structure, table definitions, column names, nor generated TypeScript code are ever logged, cached, or transmitted across the network.

How are JSON and JSONB columns converted into TypeScript?

With the "JSON as Record" toggle enabled, JSON and JSONB columns are mapped to Record<string, unknown> for seamless property access. Disabling the toggle maps them to strict unknown, prompting developers to validate payloads with schemas like Zod or Valibot before consumption.

Can I generate multiple tables simultaneously from one DDL script?

Yes. You can paste an entire database migration file or multiple CREATE TABLE blocks. The engine parses every statement into its own isolated TypeScript interface, complete with table comments, primary key attributes, and customizable prefix/suffix names.

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