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Document Structure

Ditto documents are composed of field-and-value pairs and have the following structure: 
{
   field1: value1,
   field2: value2,
   field3: value3,
   ...
   fieldN: valueN
}
The value of a field can be any of the JSON data types, including other documents, arrays, and arrays of documents. For example, the following document contains values of varying types: 
{
  _id: "0016d749-9a9b-4ece-8794-7f3eb40bc82e",
  name: "John Doe",
  age: 30,
  email: "john.doe@example.com",
  address: {
    street: "123 Main St",
    city: "Anytown",
    state: "CA",
    zip: "12345"
  },
  is_active: true,
  created_at: "2021-01-01T00:00:00Z"
}
The above fields have the following data types:
  • _id: STRING
  • name: STRING
  • age: NUMBER
  • email: STRING
  • address: OBJECT
  • is_active: BOOLEAN
  • created_at: DATE

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Identifying Documents

In Ditto, each document stored in a collection requires a unique _id field that acts as a primary key. If an inserted document omits the _id field, Ditto automatically generates a unique identifier for the _id field. Once set for a given document, the _id field cannot be changed. The same document contents inserted with a different _id will be treated as a new document within Ditto. The _id is required for all documents and can be any JSON data type. While generating a unique identifier is the default behavior, typically you will provide your own _id values represented as a more complex object (acting as a composite key). For example, the following document includes a _id field with a complex object: 
{
  _id: {
    orderId: "0016d749-9a9b-4ece-8794-7f3eb40bc82e"
    locationId: "5da42ab5-d00b-4377-8524-43e43abf9e01"
  },
  ...
}
You can then either query documents using the entire _id object or by breaking it down into its individual components.
DQL
SELECT * 
FROM orders 
WHERE _id.locationId = '5da42ab5-d00b-4377-8524-43e43abf9e01'
DQL
SELECT * 
FROM orders 
WHERE _id = {'orderId': '0016d749-9a9b-4ece-8794-7f3eb40bc82e', 'locationId': '5da42ab5-d00b-4377-8524-43e43abf9e01'}
It is important to carefully consider the _id field when designing your data model, as this is used for authorization rules within Ditto. For more information, see Authorization.

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Document Fields

Documents are composed of fields, which are key-value pairs.

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Field Names

Similar to most document-oriented databases, you can only use strings to encode field names in documents. For complete naming rules, see IDs, Paths, Strings, and Keywords.

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Field Values

Field values can be encoded using various data types, including scalar types, providing flexibility in representing a wide range of information.
Avoid using arrays in Ditto.Due to potential merge conflicts when offline peers reconnect to the mesh and attempt to sync their updates, especially when multiple peers make concurrent updates to the same item within the array.Instead using a JSON object within a MAP allows you to automatically merge the contents of the MAP when offline peers reconnect to the mesh.
Each value of a field is stored as a specific CRDT type, for example a MAP or REGISTER. You can read more about CRDTs in Syncing Data.

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Relationships

There are several methods for linking related data items and organizing them for easy lookup:
  • Field referencing another document by _id.
  • Embedded JSON object within the document.

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Foreign-Key Relationships

To create a foreign-key relationship, store the primary key to one document within another document. A foreign-key relationship establishes a link between two or more datasets. For example, if you have two collections, cars and owners, where each car has a corresponding owner, every document in the cars collection would include a field containing the ID of a document in the owners collection. For example:
Car
{
  "_id": "0016d749-9a9b-4ece-8794-7f3eb40bc82e",
  "owner_id": "5da42ab5-d00b-4377-8524-43e43abf9e01"
}
Owner
{
  "_id": "5da42ab5-d00b-4377-8524-43e43abf9e01",
  "name": "John Doe"
}

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Embedded Relationships

An embedded relationship establishes a parent-child hierarchy between embedded data elements. In this hierarchy, the key functions as the parent, and its encapsulated values, represented as a set of key-value pairs, serve as children. For example: 
{
  "_id": {
    "vin": "JTMDF4EV0FD100869",
    "make": "Toyota",
    "model": "RAV4",
    "year": 2015,
  },
  "details": {
    "engine": {
      "type": "Gasoline",
      "displacement": "1.8L"
    },
    "interior": {
      "seats": 5,
      "color": "Black"
    },
    "features": {
      "safety": {
        "airbags": 6,
        "antilockBrakes": true
      },
      "technology": {
        "infotainment": "Touchscreen",
        "navigation": true
      }
    }
  }
}