SQL to TypeScript Interface Generator — Free Online Tool

The Pain of Manual SQL-to-TypeScript Type Writing

Every full-stack developer working with TypeScript and a relational database knows this workflow: you design a table in PostgreSQL, then you need to represent it in your application code. So you open a new file and start typing interface User {. You copy over each column name. You figure out which TypeScript type maps to VARCHAR, INTEGER, TIMESTAMP, BOOLEAN, JSONB. You handle nullable columns with the optional modifier. Twenty minutes later, you have a TypeScript interface that exactly mirrors a CREATE TABLE statement you wrote an hour ago.

This is pure mechanical work. It doesn't require judgment, creativity, or deep knowledge. It's the kind of task that exists purely because the two systems — your database schema and your TypeScript type system — don't have an automatic bridge. Until you build one, or use a tool that already has.

The problem compounds as your schema evolves. You add a column to a table. Now you have to remember to update the TypeScript interface, the Zod schema, the API response type, the test fixtures. Miss one, and you get a runtime error that TypeScript's type system was supposed to prevent. The entire benefit of typed languages is undermined by the manual synchronization burden.

SQL Type Mapping: PostgreSQL to TypeScript

Before building or using a generator, it's worth understanding the type mapping manually. This table covers the most common PostgreSQL types and their TypeScript equivalents:

PostgreSQL Type	TypeScript Type	Notes
VARCHAR(n), TEXT, CHAR(n)	string	All string-like types
INTEGER, BIGINT, SMALLINT	number	Note: BIGINT can exceed JS Number precision
NUMERIC, DECIMAL, FLOAT, REAL	number	Consider string for NUMERIC to avoid float precision issues
BOOLEAN	boolean	Direct mapping
TIMESTAMP, TIMESTAMPTZ, DATE	Date or string	Depends on your ORM serialization
UUID	string	No native UUID type in TypeScript
JSON, JSONB	Record<string, unknown> or unknown	Define a specific type if schema is known
ARRAY (e.g., TEXT[])	string[]	Element type follows the scalar mapping
BYTEA	Buffer or Uint8Array	Node.js specific
SERIAL, BIGSERIAL	number	Auto-increment integer

Nullable columns (those without NOT NULL) map to type | null in TypeScript, or with the optional property modifier ? depending on your preferred convention. Optional (not present) and nullable (present but null) are semantically different and should be modeled accordingly.

A Real-World Example: Converting a Users Table

Here's a representative PostgreSQL users table:

CREATE TABLE users (
  id          UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  email       VARCHAR(255) NOT NULL UNIQUE,
  username    VARCHAR(50) NOT NULL,
  full_name   TEXT,
  avatar_url  TEXT,
  is_active   BOOLEAN NOT NULL DEFAULT true,
  role        VARCHAR(20) NOT NULL DEFAULT 'user',
  metadata    JSONB,
  created_at  TIMESTAMPTZ NOT NULL DEFAULT NOW(),
  updated_at  TIMESTAMPTZ NOT NULL DEFAULT NOW(),
  deleted_at  TIMESTAMPTZ
);

A manually written TypeScript interface might look like this:

interface User {
  id: string;
  email: string;
  username: string;
  full_name: string | null;
  avatar_url: string | null;
  is_active: boolean;
  role: string;
  metadata: Record<string, unknown> | null;
  created_at: Date;
  updated_at: Date;
  deleted_at: Date | null;
}

That's 10+ lines of mechanical conversion. The DevKits Pro SQL to TypeScript generator produces this output in under a second. Paste your CREATE TABLE, click convert, copy the output. For a schema with 20 tables, the time savings approaches a full working hour.

Beyond Basic Interfaces: Insert and Update Types

Production TypeScript codebases don't use a single type for all database operations. You need at least three variants:

// Full row as returned from SELECT
interface User {
  id: string;
  email: string;
  username: string;
  full_name: string | null;
  is_active: boolean;
  created_at: Date;
  updated_at: Date;
}

// For INSERT — omit auto-generated fields
type NewUser = Omit<User, 'id' | 'created_at' | 'updated_at'>;

// For UPDATE — all fields optional except id
type UpdateUser = Partial<Omit<User, 'id'>> & Pick<User, 'id'>;

A good SQL-to-TypeScript generator understands PRIMARY KEY, DEFAULT, and SERIAL constraints well enough to generate these variants automatically. DevKits Pro generates all three patterns from a single SQL input, saving additional manual derivation work.

SQL to Zod Schema Generation

If you're using Zod for runtime validation (common in Next.js and tRPC applications), you need Zod schemas in addition to TypeScript interfaces. The Zod schema provides runtime type-checking that TypeScript's static types can't offer — it validates that an API response or form input actually conforms to the expected shape before you process it.

import { z } from 'zod';

// Generated from the same CREATE TABLE
const UserSchema = z.object({
  id: z.string().uuid(),
  email: z.string().email().max(255),
  username: z.string().max(50),
  full_name: z.string().nullable(),
  avatar_url: z.string().url().nullable(),
  is_active: z.boolean(),
  role: z.string().max(20),
  metadata: z.record(z.unknown()).nullable(),
  created_at: z.date(),
  updated_at: z.date(),
  deleted_at: z.date().nullable(),
});

type User = z.infer<typeof UserSchema>;

DevKits Pro generates both the Zod schema and the TypeScript interface from a single SQL input, keeping them in sync automatically.

SQL to Python Dataclass and Pydantic

If you work across multiple languages — a TypeScript frontend with a Python FastAPI backend, for example — the same SQL schema needs to be represented in Python as well. Manually maintaining equivalent types in two languages is one of the most error-prone tasks in polyglot stacks.

from datetime import datetime
from typing import Optional
from uuid import UUID
from pydantic import BaseModel, EmailStr

class User(BaseModel):
    id: UUID
    email: EmailStr
    username: str
    full_name: Optional[str] = None
    avatar_url: Optional[str] = None
    is_active: bool = True
    role: str = "user"
    metadata: Optional[dict] = None
    created_at: datetime
    updated_at: datetime
    deleted_at: Optional[datetime] = None

DevKits Pro's SQL to Code generator supports TypeScript interfaces, Zod schemas, Python dataclasses, Pydantic models, and Go structs from a single SQL input — covering the most common polyglot development scenarios.

Integrating with ORMs: Drizzle, Prisma, and TypeORM

Modern TypeScript ORMs like Drizzle ORM and Prisma use their own schema definition formats and generate TypeScript types from them. If you're starting from an existing PostgreSQL database (introspecting an existing schema rather than designing from scratch), the workflow is different:

• Prisma: prisma db pull introspects your database and generates a schema.prisma file. prisma generate then produces TypeScript types from that schema.
• Drizzle ORM: drizzle-kit introspect:pg generates a schema file from your database. Types are inferred from the schema automatically.
• Manual SQL approach: When you don't have ORM integration — working with raw SQL queries, migrating from another stack, or writing standalone scripts — SQL-to-TypeScript generators fill the gap.

The DevKits SQL-to-TypeScript tool is most useful when you're outside the ORM ecosystem: writing migration scripts, building a TypeScript SDK for an existing database, or working with raw SQL and pg or mysql2 drivers directly.

How to Use the DevKits SQL to TypeScript Generator

The generator is part of DevKits Pro, available at a one-time cost of $9:

1. Go to aiforeverthing.com/pro.html and unlock Pro access
2. Open the SQL to Code tool from the Pro tools menu
3. Paste your CREATE TABLE statement (PostgreSQL, MySQL, or SQLite syntax supported)
4. Select output format: TypeScript interface, Zod schema, Pydantic model, Go struct
5. Copy the generated code

The tool handles:

• All common SQL data types with correct TypeScript mappings
• Nullable columns mapped to T | null
• Column names converted from snake_case to camelCase (optional)
• Primary key and constraint awareness for generated Insert/Update variants
• Multiple table conversion in a single session
• Export as a .ts file for direct use in your project

Writing Your Own SQL to TypeScript Converter

If you prefer to build your own converter for custom requirements, here's the core logic in TypeScript:

const SQL_TO_TS_TYPE: Record<string, string> = {
  'varchar': 'string',
  'text': 'string',
  'char': 'string',
  'integer': 'number',
  'int': 'number',
  'bigint': 'number',
  'smallint': 'number',
  'numeric': 'number',
  'decimal': 'number',
  'float': 'number',
  'real': 'number',
  'boolean': 'boolean',
  'bool': 'boolean',
  'timestamp': 'Date',
  'timestamptz': 'Date',
  'date': 'Date',
  'uuid': 'string',
  'json': 'Record<string, unknown>',
  'jsonb': 'Record<string, unknown>',
  'bytea': 'Buffer',
  'serial': 'number',
  'bigserial': 'number',
};

function parseSqlToInterface(sql: string): string {
  const tableMatch = sql.match(/CREATE TABLE (\w+)\s*\(([^;]+)\)/is);
  if (!tableMatch) throw new Error('Invalid CREATE TABLE statement');

  const tableName = tableMatch[1];
  const columnDefs = tableMatch[2];
  const typeName = toPascalCase(tableName);

  const lines = columnDefs
    .split(',')
    .map(line => line.trim())
    .filter(line => !line.match(/^(PRIMARY|UNIQUE|CHECK|FOREIGN|INDEX)/i));

  const fields = lines.map(line => {
    const parts = line.match(/^(\w+)\s+(\w+)/);
    if (!parts) return null;
    const [, colName, sqlType] = parts;
    const tsType = SQL_TO_TS_TYPE[sqlType.toLowerCase()] ?? 'unknown';
    const isNullable = !line.toUpperCase().includes('NOT NULL');
    const fieldName = toSnakeCase(colName);
    return `  ${fieldName}${isNullable ? '?' : ''}: ${tsType}${isNullable ? ' | null' : ''};`;
  }).filter(Boolean);

  return `interface ${typeName} {\n${fields.join('\n')}\n}`;
}

This covers the basic case. Production converters need to handle multi-word type names (TIMESTAMP WITH TIME ZONE), array types (TEXT[]), constraint clauses, and comments. The DevKits Pro generator handles all of these edge cases.

Frequently Asked Questions

How do I convert a SQL CREATE TABLE to a TypeScript interface?

Map each column to a TypeScript type using the SQL-to-TypeScript type mapping table above. VARCHAR, TEXT, and CHAR become string; INTEGER, BIGINT, and NUMERIC become number; BOOLEAN becomes boolean; TIMESTAMP becomes Date; UUID becomes string; JSON/JSONB become Record<string, unknown>. Add | null for nullable columns. For large schemas, use DevKits Pro to automate this conversion.

What's the best tool for generating TypeScript types from SQL?

If you're using an ORM: Prisma's prisma generate and Drizzle's introspection are the best options as they keep types in sync automatically. For raw SQL or ORM-free workflows: DevKits Pro SQL to TypeScript generator handles all common types and nullable columns in a browser-based tool with no setup required.

How should I handle BIGINT in TypeScript?

JavaScript's number type is a 64-bit float with only 53 bits of integer precision. PostgreSQL BIGINT can hold values up to 2^63 - 1, which exceeds JavaScript's safe integer range. For primary keys and foreign keys using BIGINT, consider typing them as string in TypeScript (the database driver serializes them as strings by default in most cases) or using JavaScript's native bigint type.

Do I need to regenerate TypeScript types every time I change the schema?

Yes, which is why ORM-based workflows that auto-generate types are preferable for actively evolving schemas. For more static schemas, a one-time generation with manual updates is acceptable. DevKits Pro makes regeneration fast — paste the updated schema, regenerate, copy the new types. The whole process takes under a minute for most schemas.

Can SQL to TypeScript generators handle complex types like enums?

PostgreSQL enums (CREATE TYPE status AS ENUM ('active', 'inactive', 'pending')) map to TypeScript union types: 'active' | 'inactive' | 'pending'. DevKits Pro handles enum column types by detecting the enum reference and generating the union type automatically when the enum definition is provided alongside the table definition.