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Azure Cosmos DB

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Azure Cosmos DB vs MongoDB Atlas: What are the differences?


In this article, we will compare the key differences between Azure Cosmos DB and MongoDB Atlas. Both Azure Cosmos DB and MongoDB Atlas are cloud-based database services that provide scalability and flexibility for storing and managing data. However, there are several important distinctions between the two that should be considered when making a decision on which one to use.

  1. Scalability: Azure Cosmos DB offers horizontal scalability for both read and write operations by distributing data across multiple regions. It uses automatic partitioning and provides various consistency models to optimize performance. On the other hand, MongoDB Atlas offers horizontal scalability through sharding, allowing users to distribute data across multiple servers. However, it requires manual configuration and management of the sharded cluster.

  2. Global Reach: Azure Cosmos DB has a global presence, with data centers located in multiple regions around the world. This allows for low latency access to data regardless of the user's geographical location. MongoDB Atlas, on the other hand, has a limited number of regions available, which may result in increased latency for users in certain geographical areas.

  3. Multi-Model Support: Azure Cosmos DB supports multiple data models, including document, key-value, graph, columnar, and time-series data. This flexibility enables users to choose the most appropriate data model for their specific needs and seamlessly switch between models. MongoDB Atlas focuses primarily on the document model and does not provide native support for other data models.

  4. Global Consistency: Azure Cosmos DB offers five well-defined consistency models to ensure data consistency across distributed environments. Users can choose the level of consistency required for their application, ranging from strong consistency to eventual consistency. MongoDB Atlas, on the other hand, provides eventual consistency by default and does not offer different consistency levels.

  5. Pricing Model: Azure Cosmos DB follows a throughput-based pricing model, where users pay for the amount of throughput required to support their application's workload. MongoDB Atlas, on the other hand, offers a capacity-based pricing model, where users pay for the amount of storage and processing resources allocated to their clusters.

  6. Managed Service: Azure Cosmos DB is a fully managed database service that takes care of the underlying infrastructure, backups, and updates, allowing developers to focus on building applications. MongoDB Atlas also provides a managed service but requires users to manage certain aspects such as backups and updates themselves.

In summary, Azure Cosmos DB offers greater scalability, global reach, multi-model support, and flexibility in consistency models, while MongoDB Atlas focuses primarily on the document model and offers a different pricing and managed service model. Decision on which one to choose depends on the specific requirements and preferences of the application.

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Pros of Azure Cosmos DB
Pros of MongoDB Atlas
  • 28
    Best-of-breed NoSQL features
  • 22
    High scalability
  • 15
    Globally distributed
  • 14
    Automatic indexing over flexible json data model
  • 10
    Tunable consistency
  • 10
    Always on with 99.99% availability sla
  • 7
    Javascript language integrated transactions and queries
  • 6
    Predictable performance
  • 5
    High performance
  • 5
    Analytics Store
  • 2
    Rapid Development
  • 2
    No Sql
  • 2
    Auto Indexing
  • 2
    Ease of use
  • 9
    MongoDB SaaS for and by Mongo, makes it so easy
  • 6
    Amazon VPC peering
  • 4
    MongoDB atlas is GUItool through you can manage all DB
  • 4
    Granular role-based access controls
  • 3
    Built-in data browser
  • 3
    Use it anywhere
  • 3
    Cloud instance to be worked with
  • 1
    Simple and easy to integrate

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Cons of Azure Cosmos DB
Cons of MongoDB Atlas
  • 18
  • 4
    Poor No SQL query support
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    What is Azure Cosmos DB?

    Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

    What is MongoDB Atlas?

    MongoDB Atlas is a global cloud database service built and run by the team behind MongoDB. Enjoy the flexibility and scalability of a document database, with the ease and automation of a fully managed service on your preferred cloud.

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    What companies use Azure Cosmos DB?
    What companies use MongoDB Atlas?
    See which teams inside your own company are using Azure Cosmos DB or MongoDB Atlas.
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    What tools integrate with Azure Cosmos DB?
    What tools integrate with MongoDB Atlas?

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    What are some alternatives to Azure Cosmos DB and MongoDB Atlas?
    Azure SQL Database
    It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    See all alternatives