CosmosDB vs DynamoDB: Key Differences and When to Use Each

CosmosDB is Microsoft's globally distributed, multi-model database service on Azure, while DynamoDB is Amazon's fully managed NoSQL database service. CosmosDB supports multiple data models and offers turnkey global distribution with low latency, whereas DynamoDB focuses on key-value and document data with seamless scaling on AWS.

Quick Comparison

Here is a quick side-by-side comparison of CosmosDB and DynamoDB on key factors.

Factor	Azure CosmosDB	AWS DynamoDB
Data Models	Supports multiple: document, key-value, graph, column-family	Primarily key-value and document
Global Distribution	Turnkey global distribution with multi-region writes	Global tables with multi-region replication
Consistency Models	Offers 5 consistency levels including strong and eventual	Eventually consistent by default, with optional strong consistency in single region
Scaling	Automatic and manual throughput scaling with provisioned RU/s	On-demand and provisioned capacity modes with auto scaling
Integration	Deep integration with Azure services and SDKs	Deep integration with AWS ecosystem and SDKs
Pricing Model	Based on Request Units (RU/s) and storage	Based on read/write capacity units and storage

Key Differences

CosmosDB is designed as a multi-model database service, meaning it supports various data types like documents, graphs, key-value, and column-family data all in one service. This flexibility allows developers to use the same database for different application needs. In contrast, DynamoDB focuses mainly on key-value and document data models, optimized for fast and predictable performance.

Another major difference is in global distribution. CosmosDB offers turnkey global distribution with multi-region writes and five well-defined consistency levels, including strong consistency. This means you can choose how fresh your data reads are across regions. DynamoDB provides global tables for multi-region replication but primarily offers eventual consistency, with strong consistency only within a single region.

Scaling and pricing also differ. CosmosDB uses Request Units (RU/s) to measure throughput, which abstracts read, write, and query costs into a single unit, while DynamoDB uses separate read and write capacity units. Both services support on-demand and provisioned capacity modes, but CosmosDB integrates deeply with Azure's ecosystem, and DynamoDB is tightly integrated with AWS services.

Code Comparison

Below is an example of inserting an item into CosmosDB using Azure SDK for Python.

python

from azure.cosmos import CosmosClient, PartitionKey

endpoint = "https://your-cosmos-account.documents.azure.com:443/"
key = "your-primary-key"
database_name = 'SampleDB'
container_name = 'Items'

client = CosmosClient(endpoint, key)
database = client.create_database_if_not_exists(id=database_name)
container = database.create_container_if_not_exists(
    id=container_name,
    partition_key=PartitionKey(path="/category"),
    offer_throughput=400
)

item = {
    'id': '1',
    'category': 'books',
    'title': 'Azure for Beginners'
}

container.upsert_item(item)
print("Item inserted into CosmosDB")

Output

Item inserted into CosmosDB

DynamoDB Equivalent

Here is the equivalent code to insert an item into DynamoDB using AWS SDK for Python (boto3).

python

import boto3

dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('Items')

item = {
    'id': '1',
    'category': 'books',
    'title': 'Azure for Beginners'
}

table.put_item(Item=item)
print("Item inserted into DynamoDB")

Output

Item inserted into DynamoDB

When to Use Which

Choose CosmosDB when you need multi-model support, turnkey global distribution with multiple consistency options, and deep integration with Azure services. It is ideal for applications requiring low latency reads and writes across multiple regions worldwide.

Choose DynamoDB if your application is built on AWS, requires a highly scalable key-value or document store, and benefits from AWS ecosystem integrations. It suits workloads needing simple, fast, and predictable performance with flexible scaling.

Key Takeaways

CosmosDB supports multiple data models and offers rich global distribution with strong consistency options.

DynamoDB focuses on key-value/document models with simple, scalable performance on AWS.

CosmosDB uses Request Units (RU/s) for throughput; DynamoDB uses read/write capacity units.

Choose CosmosDB for multi-region, multi-model Azure-native apps; choose DynamoDB for AWS-centric, scalable NoSQL needs.