Tanstack DB Skills Tanstack DB Schemas

Schemas

TanStack DB uses schemas to validate and transform data during mutations. Schemas are optional but strongly recommended for type safety and data integrity.

Supported Libraries

Any StandardSchema compatible library:

• Zod
• Valibot
• ArkType
• Effect Schema

Common Patterns

Basic Validation

import { z } from 'zod'
import { createCollection } from '@tanstack/react-db'
import { queryCollectionOptions } from '@tanstack/query-db-collection'

const todoSchema = z.object({
  id: z.string(),
  text: z.string().min(1, 'Text is required'),
  completed: z.boolean(),
  priority: z.number().min(0).max(5),
})

const collection = createCollection(
  queryCollectionOptions({
    schema: todoSchema,
    queryKey: ['todos'],
    queryFn: async () => api.todos.getAll(),
    getKey: (item) => item.id,
  }),
)

// Invalid data throws SchemaValidationError
collection.insert({
  id: '1',
  text: '', // ❌ Too short
  completed: 'yes', // ❌ Wrong type
  priority: 10, // ❌ Out of range
})

Default Values

const todoSchema = z.object({
  id: z.string(),
  text: z.string().min(1),
  completed: z.boolean().default(false),
  priority: z.number().default(0),
  tags: z.array(z.string()).default([]),
  created_at: z.date().default(() => new Date()),
})

// Defaults filled automatically
collection.insert({
  id: '1',
  text: 'Buy groceries',
  // completed defaults to false
  // priority defaults to 0
  // tags defaults to []
  // created_at defaults to now
})

Type Transformations

Transform input types to different output types:

const eventSchema = z.object({
  id: z.string(),
  name: z.string(),
  // IMPORTANT: Accept both input AND output types
  start_time: z
    .union([z.string(), z.date()])
    .transform((val) => (typeof val === 'string' ? new Date(val) : val)),
})

// Insert with string (TInput)
collection.insert({
  id: '1',
  name: 'Conference',
  start_time: '2024-06-15T10:00:00Z', // String in
})

// Get returns Date (TOutput)
const event = collection.get('1')
console.log(event.start_time.getFullYear()) // Date out!

TInput vs TOutput (Critical Concept)

When transforming types, TInput MUST be a superset of TOutput for updates to work:

// ❌ BAD: TInput only accepts string, but draft contains Date
const badSchema = z.object({
  created_at: z.string().transform((val) => new Date(val)),
})
// TInput:  { created_at: string }
// TOutput: { created_at: Date }
// Problem: collection.update() passes Date but schema expects string!

// ✅ GOOD: TInput accepts both string and Date
const goodSchema = z.object({
  created_at: z
    .union([z.string(), z.date()])
    .transform((val) => (typeof val === 'string' ? new Date(val) : val)),
})
// TInput:  { created_at: string | Date }
// TOutput: { created_at: Date }
// Works: update draft.created_at is Date, which TInput accepts!

Rule: If you transform A → B, use z.union([A, B]) as input.

Validation Patterns

// String constraints
z.string().min(3, 'Too short')
z.string().max(100, 'Too long')
z.string().email('Invalid email')
z.string().url('Invalid URL')
z.string().regex(/^[a-z]+$/, 'Lowercase only')

// Number constraints
z.number().int('Must be whole number')
z.number().positive('Must be positive')
z.number().min(0).max(100)

// Enums
z.enum(['low', 'medium', 'high'])

// Optional and nullable
z.string().optional() // Can be omitted
z.string().nullable() // Can be null
z.string().optional().nullable() // Either

// Arrays
z.array(z.string()).min(1, 'At least one required')

// Custom validation
z.string().refine(
  (val) => /^[a-zA-Z0-9_]+$/.test(val),
  'Only letters, numbers, underscores',
)

// Cross-field validation
z.object({
  start: z.date(),
  end: z.date(),
}).refine((data) => data.end > data.start, 'End must be after start')

Error Handling

import { SchemaValidationError } from '@tanstack/db'

try {
  collection.insert({
    id: '1',
    email: 'invalid',
    age: -5,
  })
} catch (error) {
  if (error instanceof SchemaValidationError) {
    console.log(error.type) // 'insert' or 'update'
    console.log(error.message) // 'Validation failed with 2 issues'
    console.log(error.issues) // Array of issues
    // [
    //   { path: ['email'], message: 'Invalid email' },
    //   { path: ['age'], message: 'Must be positive' }
    // ]
  }
}

React Form Example

function TodoForm() {
  const [errors, setErrors] = useState<Record<string, string>>({})

  const handleSubmit = (e: React.FormEvent) => {
    e.preventDefault()
    setErrors({})

    try {
      todoCollection.insert({
        id: crypto.randomUUID(),
        text: e.currentTarget.text.value,
        priority: parseInt(e.currentTarget.priority.value),
      })
    } catch (error) {
      if (error instanceof SchemaValidationError) {
        const newErrors: Record<string, string> = {}
        error.issues.forEach((issue) => {
          const field = issue.path?.[0] || 'form'
          newErrors[field] = issue.message
        })
        setErrors(newErrors)
      }
    }
  }

  return (
    <form
      <input name="text" />
      {errors.text && <span className="error">{errors.text}</span>}

      <input name="priority" type="number" />
      {errors.priority && <span className="error">{errors.priority}</span>}

      <button type="submit">Add</button>
    </form>
  )
}

Schema with Computed Fields

const productSchema = z
  .object({
    id: z.string(),
    name: z.string(),
    base_price: z.number(),
    discount_percent: z.number().default(0),
  })
  .transform((data) => ({
    ...data,
    final_price: data.base_price * (1 - data.discount_percent / 100),
    display_price: `$${(data.base_price * (1 - data.discount_percent / 100)).toFixed(2)}`,
  }))

collection.insert({
  id: '1',
  name: 'Widget',
  base_price: 100,
  discount_percent: 10,
})

const product = collection.get('1')
console.log(product.final_price) // 90
console.log(product.display_price) // '$90.00'

Handlers Receive TOutput

Schema transforms happen BEFORE handlers run:

const schema = z.object({
  id: z.string(),
  created_at: z
    .union([z.string(), z.date()])
    .transform((val) => (typeof val === 'string' ? new Date(val) : val)),
})

const collection = createCollection({
  schema,
  onInsert: async ({ transaction }) => {
    const item = transaction.mutations[0].modified
    // item.created_at is already a Date (TOutput)!

    // If API needs string, serialize it
    await api.create({
      ...item,
      created_at: item.created_at.toISOString(),
    })
  },
})

Important Notes

• Schemas validate client mutations only (insert/update), not server data
• TypeScript types are inferred from schema automatically
• If you provide a schema, don't also pass explicit type parameter
• Keep transformations simple—they run synchronously on every mutation

Detailed References