Azure Cosmos DB (SQL API)

1. Introduction

Azure Cosmos DB is a globally distributed, multi-model database service designed to provide high availability, low latency, and scalability. It supports various APIs, including SQL, MongoDB, Cassandra, Gremlin, and Table storage. This lesson focuses on the SQL API of Azure Cosmos DB, which allows for SQL-like queries.

2. Key Concepts

• **Database:** A container for documents. Each database can have multiple containers.
• **Container:** A collection of documents that can be queried. Containers are schema-agnostic.
• **Document:** The basic unit of data in Cosmos DB, stored in JSON format.
• **Throughput:** Measured in Request Units (RU/s), which determines the performance and scalability.
• **Consistency Levels:** Defines the guarantees about the visibility of writes across replicas.

3. Installation

To start using Azure Cosmos DB, follow these steps:

1. Sign in to the Azure Portal.
2. Select "Create a resource" and choose "Azure Cosmos DB".
3. Choose the "SQL API" as the database type.
4. Configure the database settings (resource group, database name, etc.).
5. Review and create the Cosmos DB account.

4. Usage

Once your database is created, you can interact with it using the Azure Cosmos DB SQL API. Here’s a simple example of how to use it:

            // Sample JavaScript code to interact with Azure Cosmos DB

            const { CosmosClient } = require("@azure/cosmos");
            const endpoint = "your-endpoint";
            const key = "your-key";
            const client = new CosmosClient({ endpoint, key });

            async function queryItems() {
                const database = client.database("your-database");
                const container = database.container("your-container");
                const query = "SELECT * from c WHERE c.id = '1'";
                
                const { resources: results } = await container.items.query(query).fetchAll();
                console.log(results);
            }

            queryItems();
            

5. Best Practices

• Design your containers based on your access patterns.
• Choose an appropriate consistency level based on your needs.
• Monitor and adjust throughput as necessary.
• Utilize partitioning effectively for larger datasets.
• Regularly back up your data to prevent loss.

6. FAQ

7. Flowchart

        graph TD;
            A[Start] --> B{Create Database}
            B -->|Yes| C[Configure Settings]
            B -->|No| D[End]
            C --> E[Create Container]
            E --> F[Add Documents]
            F --> G{Query Data}
            G -->|Yes| H[Retrieve Results]
            G -->|No| D