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Azure Cosmos DB

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Azure Cosmos DB vs Azure SQL Database: What are the differences?

Azure Cosmos DB and Azure SQL Database are both widely used database services offered by Microsoft Azure. While they serve the purpose of storing and managing data, there are several key differences between these two services that determine when and how they should be used.

  1. Scalability and Performance: Azure Cosmos DB is designed to scale horizontally across multiple regions and provide global distribution of data with low latency. It offers limitless elastic scalability and can handle massive amounts of throughput. On the other hand, Azure SQL Database is built for vertical scalability within a single region and has certain limitations on scalability and performance.

  2. Data Model: Azure Cosmos DB follows a NoSQL document data model, where data is stored in flexible JSON-like documents. It supports schema-less data and can handle unstructured, semi-structured, and structured data. In contrast, Azure SQL Database follows a relational data model, where data is organized into tables with predefined schemas that enforce data integrity and relationships.

  3. Consistency Models: Azure Cosmos DB provides several consistency models, including strong, bounded staleness, session, and eventual consistency. This allows developers to choose the level of consistency that best suits their application requirements. Azure SQL Database, on the other hand, offers strong consistency by default, ensuring that every read operation retrieves the latest committed data.

  4. Querying Capabilities: Azure Cosmos DB comes with a powerful querying capability using SQL-like syntax, which allows developers to perform complex queries on the stored documents using a familiar language. It also provides support for NoSQL-specific operations like filtering, sorting, and projecting on nested properties. In contrast, Azure SQL Database supports traditional SQL queries that are optimized for relational data and come with powerful querying capabilities for joins, aggregations, and complex filtering.

  5. Multimodel Support: Azure Cosmos DB is a multimodel database that supports multiple APIs including SQL, MongoDB, Cassandra, Gremlin, and Table. This means that developers can choose the API that suits their application and work with their preferred programming model. Azure SQL Database, on the other hand, primarily supports the relational SQL API and is focused on supporting relational data storage and retrieval.

  6. Cost Model: Azure Cosmos DB is billed based on provisioned throughput and consumed storage, which allows for precise control over the resources used and can be cost-effective for applications with varying workload patterns. Azure SQL Database, on the other hand, is billed based on the compute and storage resources provisioned, which may result in higher costs for fluctuating workloads or for applications that require high scalability.

In Summary, Azure Cosmos DB and Azure SQL Database differ in scalability, data models, consistency models, querying capabilities, multimodel support, and cost models, enabling developers to select the most suitable database service for their specific needs.

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Pros of Azure Cosmos DB
Pros of Azure SQL Database
  • 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
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable

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Cons of Azure Cosmos DB
Cons of Azure SQL Database
  • 18
    Pricing
  • 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 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.

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

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    What are some alternatives to Azure Cosmos DB and Azure SQL Database?
    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.
    Cassandra
    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