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Azure Cosmos DB

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Azure Storage

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Azure Cosmos DB vs Azure Storage: What are the differences?

Azure Cosmos DB and Azure Storage are cloud-based storage services. They differ in terms of their data models, scalability, querying capabilities, and storage options. Here are the key differences between them:

  1. Data Model: Azure Cosmos DB is a globally distributed, multi-model database service that supports various data models, including key-value, document, columnar, and graph. Azure Storage, on the other hand, primarily offers a simple object storage service with a key-value data model. It is designed for storing unstructured data such as blobs, files, queues, and tables.

  2. Scalability: Azure Cosmos DB is built for global scalability and can automatically scale throughput and storage across multiple regions. It offers elastic scalability with fine-grained control over performance and cost. Azure Storage also provides scalability, but it requires manual configuration and management of storage accounts and blob containers to handle increased load. Scaling Azure Storage may involve sharding data across multiple storage accounts.

  3. Querying Capabilities: Azure Cosmos DB supports rich query capabilities across various data models. It provides a SQL-like query language called SQL API for querying JSON documents. It also supports other APIs like Gremlin for graph data and MongoDB API for document-oriented querying. Azure Storage, on the other hand, does not offer built-in query capabilities. Retrieving data from Azure Storage typically involves directly accessing the stored objects using their unique keys.

  4. Storage Options: Azure Cosmos DB provides storage for application data, along with built-in features like automatic indexing, data partitioning, and replication. It is a fully managed service that abstracts away the underlying storage implementation. Azure Storage, on the other hand, offers different types of storage options, including Blob storage for large object data, Queue storage for messaging, Table storage for structured NoSQL data, and File storage for file shares.

  5. Consistency Models: Azure Cosmos DB offers multiple consistency models, allowing developers to choose the desired level of data consistency based on their application requirements. It provides options like strong consistency, bounded staleness, session consistency, and eventual consistency. Azure Storage, on the other hand, primarily provides eventual consistency for read operations. It may take some time for changes made to Azure Storage to propagate across different regions.

In summary, Azure Cosmos DB is a globally distributed database service with support for multiple data models, automatic scalability, rich querying capabilities, and various consistency models. It is suitable for applications requiring high performance, global reach, and flexible data models. Azure Storage, on the other hand, is a scalable object storage service focused on unstructured data storage. It provides storage options like blobs, queues, tables, and files, but lacks the querying capabilities and flexibility of Azure Cosmos DB.

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Pros of Azure Cosmos DB
Pros of Azure Storage
  • 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
  • 24
    All-in-one storage solution
  • 15
    Pay only for data used regardless of disk size
  • 9
    Shared drive mapping
  • 2
    Cost-effective
  • 2
    Cheapest hot and cloud storage

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Cons of Azure Cosmos DB
Cons of Azure Storage
  • 18
    Pricing
  • 4
    Poor No SQL query support
  • 2
    Direct support is not provided by Azure storage

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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 Azure Storage?

Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.

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

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What are some alternatives to Azure Cosmos DB and Azure Storage?
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 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.
MongoDB
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
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.
MySQL
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.
See all alternatives