Azure Cosmos DB vs MongoDB Atlas
When it comes to cloud-based databases, two big names always come to mind - Azure Cosmos DB and MongoDB Atlas. Both of these databases offer robust features and functionality for modern applications while being scalable, reliable and provide high performance.
In this blog post, we will compare these two databases and help you decide which one is a better fit for your workloads based on their strengths and weaknesses.
Technical Details
Azure Cosmos DB
Azure Cosmos DB is a globally-distributed, multi-model database service that provides high performance, reliability, and availability with various APIs to store and query data. This service can be used to store unstructured, semi-structured, and structured data without requiring any schema or indexing beforehand.
Key Features:
- Automatic and instant scaling
- Multi-master replication and high consistency
- Global distribution and low latency
- Multiple APIs support, including SQL, MongoDB, Cassandra, and more
- Multiple data models: Document, Key-Value, Graph, Column-Family
MongoDB Atlas
MongoDB Atlas is a fully managed cloud database service that runs on AWS, Azure, or Google Cloud Platform. It provides a scalable database that is designed to support high performance, availability, and reliability. Atlas uses a document-oriented data model, which allows for flexible schema design and makes it easy to work with semi-structured data.
Key Features:
- Fully managed and scalable with automatic sharding
- Cross-region replication and built-in backup and restore
- Seamless integration with AWS, Azure, and Google Cloud
- Data compression and encryption
- Powerful aggregation and query support
Performance and Scalability
Azure Cosmos DB
Azure Cosmos DB offers automatic and instant scaling, which means that you don't need to worry about capacity planning, and you can seamlessly scale resources up or down based on the demand. Cosmos DB provides low-latency responses to queries due to its global distribution, which means that you can access your data from anywhere in the world with negligible latency. Cosmos DB supports multi-master replication, which ensures that all copies of the data are updated simultaneously and can handle millions of transactions per second.
MongoDB Atlas
MongoDB Atlas also provides automatic scaling with integrated sharding, which allows you to scale resources horizontally without any downtime. Atlas has a predictable performance with a latency of fewer than 10 milliseconds, which is faster than many database solutions. Atlas uses cross-region replication, which helps you to ensure data availability in the event of a failure. Atlas can handle up to 100,000 reads and writes per second, making it suitable for applications of any size.
Pricing
Azure Cosmos DB
Azure Cosmos DB pricing is based on the amount of data stored, the number of transactions, and the throughput. With Cosmos DB, you can choose between different pricing tiers based on your needs, including free tier for a small amount of data storage and throughput, and provisioned throughput pricing model for larger workloads.
MongoDB Atlas
MongoDB Atlas pricing is based on the size of your cluster and the amount of data stored. Atlas has free and paid tiers based on your consumption, and you can add capacity on-demand by increasing the number of nodes.
Conclusion
Both Azure Cosmos DB and MongoDB Atlas are leading cloud-based database options in the market, and both have their strengths and weaknesses. Cosmos DB offers multiple models and APIs and has low latency due to global distribution, while Atlas offers a document-oriented model and seamless integration with AWS, Azure, and Google Cloud.
When selecting a cloud-based database service, it's essential to consider your specific requirements, including data models, APIs, performance, scalability, and pricing. However, both Azure Cosmos DB and MongoDB Atlas provide robust features and functionality for modern applications, making them an ideal option for developers.
References: