The Document data type in DynamoDB is a powerful feature that allows you to store complex and hierarchical data structures in a single attribute. This attribute can then be easily retrieved and manipulated using the DynamoDB API.
What is the Document data type?
The Document data type is a way to store structured data within a single attribute in DynamoDB. It allows you to represent complex objects, such as JSON-like structures, without the need for additional tables or attributes. This makes it an ideal choice for scenarios where you have varying or dynamic data requirements.
When using the Document data type, you can nest values inside other values, creating a hierarchy of attributes. Each attribute within the hierarchy can have its own data type, including strings, numbers, booleans, lists, and even other documents.
The Document data type offers flexibility and simplicity by providing a unified way to store and retrieve structured data. It eliminates the need for complex table designs or additional queries to fetch related information.
What does the Document data type contain?
The Document data type contains key-value pairs, where each key represents an attribute name and each value represents the corresponding value of that attribute. The value itself can be of any supported DynamoDB data type.
Let’s take an example:
{
"customer_id": "123456",
"name": {
"first_name": "John",
"last_name": "Doe"
},
"age": 30,
"orders": [
{
"order_id": "order_001",
"product": "XYZ",
"quantity": 2
},
{
"order_id": "order_002",
"product": "ABC",
"quantity": 1
}
],
"active": true
}
In this example, the Document data type contains various attributes. The customer_id attribute is a string, while the name attribute is itself a nested document with two sub-attributes – first_name and last_name. The age attribute is a number, the orders attribute is an array of nested documents representing orders, and the active attribute is a boolean value.
Nested Documents and Lists
The Document data type allows you to nest documents within documents, creating complex hierarchical structures. In our example above, the name attribute is a nested document within the main document. Similarly, the orders attribute contains an array of nested documents representing multiple orders.
You can access individual elements within lists or nested documents using dot notation or indexing. For example, to access the first name of the customer in our example above, you can use:
document.name.first_name
This will return “John”. Similarly, to access the product name of the second order in our example:
document.orders[1].product
This will return “ABC”. By leveraging this capability of DynamoDB’s Document data type, you can easily navigate and manipulate complex data structures.
In conclusion
The Document data type in DynamoDB provides a flexible and efficient way to store structured data without requiring additional tables or attributes. It allows you to represent complex objects with ease by leveraging hierarchical structures and nesting capabilities. With support for different data types and easy navigation through dot notation or indexing, the Document data type is a powerful tool for managing complex data in DynamoDB.