Schemas

A schema is a description of

1. the tables in your Convex project
2. the type of documents within your tables

While it is possible to use Convex without defining a schema, adding a schema.ts file will ensure that the documents in your tables are the correct type. If you're using TypeScript, adding a schema will also give you end-to-end type safety throughout your app.

We recommend beginning your project without a schema for rapid prototyping and then adding a schema once you've solidified your plan. To learn more see our Schema Philosophy.

Example: TypeScript and Schemas

Writing schemas

Schemas are defined in a schema.ts file in your convex/ directory and look like:

convex/schema.ts

import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  messages: defineTable({
    body: v.string(),
    user: v.id("users"),
  }),
  users: defineTable({
    name: v.string(),
    tokenIdentifier: v.string(),
  }).index("by_token", ["tokenIdentifier"]),
});

This schema (which is based on our users and auth example), has 3 tables: channels, messages, and users. Each table is defined using the defineTable function. Within each table, the document type is defined using the validator builder, v. In addition to the fields listed, Convex will also automatically add _id and _creationTime fields. To learn more, see System Fields.

Generating a Schema

While writing your schema, it can be helpful to consult the Convex Dashboard. The "Generate Schema" button in the "Data" view suggests a schema declaration based on the data in your tables.

Validators

The validator builder, v is used to define the type of documents in each table. It has methods for each of Convex's types:

convex/schema.ts

import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  documents: defineTable({
    id: v.id("documents"),
    string: v.string(),
    number: v.number(),
    boolean: v.boolean(),
    nestedObject: v.object({
      property: v.string(),
    }),
  }),
});

It additionally allows you to define unions, optional property, string literals, and more. Argument validation and schemas both use the same validator builder, v.

Optional fields

You can describe optional fields by wrapping their type with v.optional(...):

defineTable({
  optionalString: v.optional(v.string()),
  optionalNumber: v.optional(v.number()),
});

This corresponds to marking fields as optional with ? in TypeScript.

Unions

You can describe fields that could be one of multiple types using v.union:

defineTable({
  stringOrNumber: v.union(v.string(), v.number()),
});

If your table stores multiple different types of documents, you can use v.union at the top level:

defineTable(
  v.union(
    v.object({
      kind: v.literal("StringDocument"),
      value: v.string(),
    }),
    v.object({
      kind: v.literal("NumberDocument"),
      value: v.number(),
    }),
  ),
);

In this schema, documents either have a kind of "StringDocument" and a string for their value:

{
  "kind": "StringDocument",
  "value": "abc"
}

or they have a kind of "NumberDocument" and a number for their value:

{
  "kind": "NumberDocument",
  "value": 123
}

Literals

Fields that are a constant can be expressed with v.literal:

defineTable({
  oneTwoOrThree: v.union(
    v.literal("one"),
    v.literal("two"),
    v.literal("three"),
  ),
});

Any

Fields or documents that could take on any value can be represented with v.any():

defineTable({
  anyValue: v.any(),
});

This corresponds to the any type in TypeScript.

Options

These options are passed as part of the options argument to defineSchema.

schemaValidation: boolean

Whether Convex should validate at runtime that your documents match your schema.

By default, Convex will enforce that all new and existing documents match your schema.

You can disable schemaValidation by passing in schemaValidation: false:

defineSchema(
  {
    // Define tables here.
  },
  {
    schemaValidation: false,
  },
);

When schemaValidation is disabled, Convex will not validate that new or existing documents match your schema. You'll still get schema-specific TypeScript types, but there will be no validation at runtime that your documents match those types.

strictTableNameTypes: boolean

Whether the TypeScript types should allow accessing tables not in the schema.

By default, the TypeScript table name types produced by your schema are strict. That means that they will be a union of strings (ex. "messages" | "channels") and only support accessing tables explicitly listed in your schema.

Sometimes it's useful to only define part of your schema. For example, if you are rapidly prototyping, it could be useful to try out a new table before adding it your schema.ts file.

You can disable strictTableNameTypes by passing in strictTableNameTypes: false:

defineSchema(
  {
    // Define tables here.
  },
  {
    strictTableNameTypes: false,
  },
);

When strictTableNameTypes is disabled, the TypeScript types will allow access to tables not listed in the schema and their document type will be any.

Regardless of the value of strictTableNameTypes, your schema will only validate documents in the tables listed in the schema. You can still create and modify documents in other tables in JavaScript or on the dashboard (they just won't be validated).

Schema validation

Schemas are pushed automatically in npx convex dev and npx convex deploy.

The first push after a schema is added or modified will validate that all existing documents match the schema. If there are documents that fail validation, the push will fail.

After the schema is pushed, Convex will validate that all future document inserts and updates match the schema.

Schema validation is skipped if schemaValidation is set to false.

Note that schemas only validate documents in the tables listed in the schema. You can still create and modify documents in other tables (they just won't be validated).

Circular references

You might want to define a schema with circular ID references like:

convex/schema.ts

import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  users: defineTable({
    preferencesId: v.id("preferences"),
  }),
  preferences: defineTable({
    userId: v.id("users"),
  }),
});

In this schema, documents in the users table contain a reference to documents in preferences and vice versa.

Because schema validation enforces your schema on every db.insert, db.replace, and db.patch call, creating circular references like this is not possible.

The easiest way around this is to make one of the references nullable:

convex/schema.ts

import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  users: defineTable({
    preferencesId: v.id("preferences"),
  }),
  preferences: defineTable({
    userId: v.union(v.id("users"), v.null()),
  }),
});

This way you can create a preferences document first, then create a user document, then set the reference on the preferences document:

convex/users.ts

TS

import { mutation } from "./_generated/server";

export default mutation(async (ctx) => {
  const preferencesId = await ctx.db.insert("preferences", {});
  const userId = await ctx.db.insert("users", { preferencesId });
  await ctx.db.patch(preferencesId, { userId });
});

Let us know if you need better support for circular references.

TypeScript types

Once you've defined a schema, npx convex dev will produce new versions of dataModel.d.ts and server.d.ts with types based on your schema.

Doc<TableName>

The Doc TypeScript type from dataModel.d.ts provides document types for all of your tables. You can use these both when writing Convex functions and in your React components:

MessageView.tsx

import { Doc } from "../convex/_generated/dataModel";

function MessageView(props: { message: Doc<"messages"> }) {
  ...
}

If you need the type for a portion of a document, use the Infer type helper.

query and mutation

The query and mutation functions in server.js have the same API as before but now provide a db with more precise types. Functions like db.insert(table, document) now understand your schema. Additionally database queries will now return the correct document type (not any).

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