Amazon S3 vs Azure Cosmos DB: What are the differences?

Key differences between Amazon S3 and Azure Cosmos DB

Amazon S3 and Azure Cosmos DB are two popular cloud services that offer different functionalities. Below are six key differences between these services:

1. Data Model: Amazon S3 is an object storage service that allows you to store and retrieve data as objects. It does not provide database capabilities and is not suitable for real-time queries or complex data relationships. On the other hand, Azure Cosmos DB is a globally distributed multi-model database service that supports document, key-value, column-family, and graph data models. It offers flexible data representation and allows for rich querying capabilities.

2. Scalability: Amazon S3 is known for its high scalability, allowing you to store and retrieve vast amounts of data. However, it does not scale automatically based on demand and requires manual capacity management. In contrast, Azure Cosmos DB offers automatic horizontal scaling, where you can simply configure the desired throughput and the service will handle the scaling automatically, ensuring consistent performance.

3. Consistency: Amazon S3 provides eventual consistency for read-after-write, meaning that changes made to an object may not be immediately reflected when reading it. This makes it suitable for scenarios where strong consistency is not required. On the other hand, Azure Cosmos DB offers multiple consistency models to choose from, including strong, eventual, bounded staleness, and session consistency, allowing you to tailor the consistency level according to your application requirements.

4. Global Distribution: Amazon S3 allows you to store and retrieve data from various regions, but it does not provide built-in global distribution capabilities. In contrast, Azure Cosmos DB is designed for global distribution out of the box, allowing you to replicate data across multiple regions with low latency and high availability. It also offers automatic data synchronization and multi-master replication, ensuring data consistency across regions.

5. Query Language: Amazon S3 does not provide a built-in query language. While you can use external tools to process and analyze the stored objects, you cannot perform complex queries directly on the data. In comparison, Azure Cosmos DB provides a rich query language called SQL-like DocumentDB API, which allows you to perform powerful queries, joins, projections, and aggregations on the data.

6. Pricing Model: Amazon S3 follows a simple pricing model based on the amount of storage used and the number of requests made. Additionally, you may incur costs for data transfers and data retrieval. Azure Cosmos DB, on the other hand, has a more complex pricing model that considers factors like throughput, storage, and data transfer. It offers different pricing tiers based on your needs, allowing you to choose the most cost-effective option for your application.

In summary, while Amazon S3 is a scalable object storage service suitable for storing and retrieving objects, Azure Cosmos DB is a globally distributed multi-model database that offers rich querying and data modeling capabilities, automatic scaling, multiple consistency levels, global distribution, a built-in query language, and a more complex pricing model.