Azure Cosmos DB vs MongoDB: What are the differences?
Azure Cosmos DB and MongoDB are both NoSQL databases that are widely used for storing and managing large amounts of unstructured and semi-structured data. While they share some similarities, there are several key differences between the two.
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Scalability:
Azure Cosmos DB offers global distribution of data, allowing users to replicate their data across multiple data centers worldwide. This enables high availability and low latency access to data. On the other hand, MongoDB relies on sharding for scaling horizontally. Sharding requires manually partitioning data across multiple servers, which can be complex to set up and manage.
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Consistency Models:
Azure Cosmos DB supports multiple consistency models, including strong consistency, eventual consistency, and session consistency. This allows developers to choose the consistency level that best fits their application's requirements. MongoDB, on the other hand, primarily uses eventual consistency by default, although it does offer support for stronger consistency guarantees.
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Query Language:
Azure Cosmos DB supports multiple APIs and query languages, including SQL, MongoDB's API, Gremlin for graph data, and Cassandra API. This allows developers to use the query language and API that they are most familiar with. MongoDB, on the other hand, uses its own query language, which is similar to JavaScript and specifically designed for querying and manipulating JSON-like documents.
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Data Modeling:
Azure Cosmos DB provides a schema-agnostic data model, allowing users to store different types of data in the same collection without the need for a predefined schema. This flexibility is particularly useful in scenarios where the data schema might evolve over time. MongoDB also supports schema flexibility, but it does require a document schema to be defined and enforced at the collection level.
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Multi-document Transactions:
Azure Cosmos DB supports multi-document transactions, allowing users to perform atomic operations across multiple documents within a single transaction. This ensures consistency and data integrity in scenarios where data across multiple documents needs to be updated together. MongoDB, on the other hand, only recently added support for multi-document transactions, starting from version 4.0.
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Pricing Model:
Azure Cosmos DB offers a pay-as-you-go pricing model based on the resources used, including storage, throughput, and data transfer. Users can scale up or down based on their workload demands. MongoDB, on the other hand, uses a subscription-based pricing model, where users need to purchase licenses based on the number of servers or how much data they need to store.
In summary, Azure Cosmos DB provides a globally distributed and highly scalable database with support for multiple consistency models and query languages, while also offering flexibility in data modeling and multi-document transactions. MongoDB, on the other hand, offers a more traditional sharded database with eventual consistency by default, but also supports schema flexibility and has recently added support for multi-document transactions.
