Develop a design by storing multiple related entities in the same document

When developing native applications using Microsoft Azure Cosmos DB, one important aspect to consider is how to design and implement the storage of multiple related entities within the same document. This approach can greatly simplify data retrieval and management, allowing for more efficient and scalable application architectures.

Azure Cosmos DB is a globally distributed, multi-model database service that supports various data models including documents, key-value, graph, and column-family. In this article, we will focus on designing and implementing the storage of related entities using the document data model.

Getting Started

To get started, you first need to create a new Azure Cosmos DB account and database. Once you have these set up, you can define a collection to store your documents. In this case, we will use the SQL API to interact with the document model.

Scenario: Blog Application

Let’s consider a scenario where we have a blog application. We want to store blog posts along with their associated comments. Each blog post can have multiple comments, and we want to retrieve both the post and its comments efficiently.

To achieve this, we can store the blog post and its comments as separate entities within the same document. Here’s an example of a document structure for a blog post:

{
"id": "blog_post_1",
"title": "Designing and Implementing Native Applications Using Azure Cosmos DB",
"content": "Lorem ipsum dolor sit amet, consectetur adipiscing elit...",
"comments": [
{
"id": "comment_1",
"text": "Great article!",
"author": "John Doe"
},
{
"id": "comment_2",
"text": "I found this very helpful. Thanks!",
"author": "Jane Smith"
}
]
}

In this example, the “comments” field is an array that contains individual comment objects. Each comment object has its own properties like “id,” “text,” and “author.”

When querying this document, you can retrieve both the blog post and its associated comments in a single document read operation. This approach eliminates the need for separate read operations to retrieve the related entities, improving performance and reducing latency.

Here’s an example of a SQL query to retrieve a blog post with its comments:

SELECT * FROM c WHERE c.id = 'blog_post_1'

This query will return the entire document, including the blog post and all its associated comments.

Updating the Document

To update the document with a new comment, you can retrieve the document, add the new comment to the “comments” array, and then replace the entire document.

POST /dbs/{db-id}/colls/{coll-id}/docs/?v=1.1 HTTP/1.1
Host: {endpoint}
Content-Type: application/json
Authorization: {masterKey}

{
"id": "blog_post_1",
"comments": [
{
"id": "comment_3",
"text": "Nice article!",
"author": "David Johnson"
}
]
}

This request replaces the existing document with the updated version containing the new comment.

Consistency Models

By storing related entities within the same document, you can take advantage of Azure Cosmos DB’s consistency models. You can choose from five different consistency levels to balance between performance and data consistency requirements. This flexibility allows you to design robust and scalable native applications.

Conclusion

When designing and implementing native applications using Azure Cosmos DB, consider storing multiple related entities in the same document. This approach simplifies data retrieval, improves performance, and enhances scalability. Azure Cosmos DB provides the flexibility and scalability needed to handle diverse application scenarios.