Building Models

Understanding requirements

Let us assume we have a student data with given Schema that we need to store in database :

{
    "id":{
        "type":"objectId",
        "required":true,
    },
    "name":{
       "type":"string",
       "required":true,
    },
    "age":{
        "type":"number",
        "required":true,
    },
    "subjects":{
        "type":"string[]",
        "required":true,
    },
    "address":{
        "city":{
            "type":"string",
            "required":true,
        },
        "state":{
            "type":"string",
            "required":true,
        }
    }

}

To build the model with given schema above follow these steps :

1. Navigate to Models screen from Application Layer -> Models.

2. Click on Create Model button and configure models name, description and model type as per your preference. For instance, if you would like to build the Student's DB model above, you can select Database Collection model type. You can check other model types here.

3. After model is created navigate to Schema tab on top of model details page.

4. You can now start building your model's schema.

Models schema for above requirements would appear something like this :

model schema

Supported data types in schema builder

• ObjectID: An ObjectID is a unique 12-byte identifier typically represented as a hexadecimal string. These are used to uniquely identify documents in a collection. This can also be used when making references to other IDs of other collections (for ex. a record in Orders collection could have a userId: ObjectId )

• Boolean: Boolean is often used to express binary decisions or states i.e. True or False.

• String: A string data type represents text. It can contain letters, numbers, symbols, and spaces. Strings are used to store textual information.

• Integer: An integer data type represents whole numbers, both positive and negative, without floating points.

• Float: A float data type represents decimal numbers. Unlike integers, floats can have fractional parts. They are used for calculations involving real numbers.

• Nested: The "Nested" type typically refers to nested or embedded structures within a data model. Unlike Dict it has a defined schema.

• Array: An array is a collection of elements of the same data type, ordered by an index. These are used to store multiple values in a single key.

• Dict: A dictionary is a collection of key-value pairs. This is different from Nested, as a Dict is a open ended object and can accept any sub fields, whereas Nested has a defined schema.

Some model types have restrictions of types of properties you can use. For for more information, please check here.