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Azure Cosmos DB vs Microsoft SQL Server: What are the differences?

Introduction

Azure Cosmos DB and Microsoft SQL Server are both popular databases offered by Microsoft. While they serve the purpose of storing and managing data, there are several key differences between them.

  1. Scalability: Azure Cosmos DB is designed to be highly scalable, allowing it to handle massive amounts of data and transactions across multiple regions. It uses a globally distributed architecture that enables automatic scaling and replication. On the other hand, Microsoft SQL Server is more suitable for smaller to mid-sized applications, as it is not as easily scalable and requires manual configuration for scaling.

  2. Data Model: Azure Cosmos DB is a NoSQL database that supports various data models, including key-value, document, column-family, and graph. This provides flexibility in storing and retrieving data based on the specific requirements of the application. In contrast, Microsoft SQL Server follows a relational data model, where data is organized into tables with predefined schemas. This structure is best suited for applications that require strict data integrity and complex relationships between entities.

  3. Availability: Azure Cosmos DB offers a high level of availability with its global distribution and multi-region replication. It provides automatic failover and data redundancy, ensuring minimal downtime and data loss in the event of a failure. On the other hand, Microsoft SQL Server's availability relies on the infrastructure it is deployed on, requiring manual configuration for achieving high availability through technologies like clustering or replication.

  4. Consistency: Azure Cosmos DB provides multiple consistency models to choose from, including strong, bounded staleness, session, and eventual consistency. These models allow developers to balance between data consistency and performance based on their application requirements. In contrast, Microsoft SQL Server follows the ACID (Atomicity, Consistency, Isolation, Durability) properties, providing strong consistency by default.

  5. Developer-friendly: Azure Cosmos DB offers extensive support for different programming models and API interfaces, making it easier for developers to work with. It supports popular languages and frameworks like .NET, Java, Node.js, and RESTful APIs. On the other hand, Microsoft SQL Server primarily uses the Transact-SQL (T-SQL) language, which requires developers to have knowledge and experience in SQL programming.

  6. Cost: Azure Cosmos DB's pricing model is based on throughput and storage consumption, allowing users to pay for the resources they need. It offers different pricing tiers and flexibility in scaling resources up or down based on demand. In contrast, Microsoft SQL Server follows a traditional licensing model, where users purchase licenses based on the edition and number of cores. This can be more expensive for larger deployments and may require additional investment for hardware infrastructure.

In summary, Azure Cosmos DB and Microsoft SQL Server differ significantly in terms of scalability, data models, availability, consistency, developer-friendliness, and cost. While Azure Cosmos DB offers high scalability, flexible data models, and automatic availability, Microsoft SQL Server provides a relational data model, strong consistency, and familiarity with SQL programming.

Advice on Azure Cosmos DB and Microsoft SQL Server

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

  1. I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
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Replies (6)

Hi Erin,

Honestly both databases will do the job just fine. I personally prefer Postgres.

Much more important is how you store the audio. While you could technically use a blob type column, it's really not ideal to be storing audio files which are "several hours long" in a database row. Instead consider storing the audio files in an object store (hosted options include backblaze b2 or aws s3) and persisting the key (which references that object) in your database column.

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Aaron Westley
Recommends
on
PostgreSQLPostgreSQL

Hi Erin, Chances are you would want to store the files in a blob type. Both MySQL and Postgres support this. Can you explain a little more about your need to store the files in the database? I may be more effective to store the files on a file system or something like S3. To answer your qustion based on what you are descibing I would slighly lean towards PostgreSQL since it tends to be a little better on the data warehousing side.

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Christopher Wray
Web Developer at Soltech LLC · | 3 upvotes · 450.3K views
Recommends
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DirectusDirectus
at

Hey Erin! I would recommend checking out Directus before you start work on building your own app for them. I just stumbled upon it, and so far extremely happy with the functionalities. If your client is just looking for a simple web app for their own data, then Directus may be a great option. It offers "database mirroring", so that you can connect it to any database and set up functionality around it!

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Julien DeFrance
Principal Software Engineer at Tophatter · | 3 upvotes · 449.9K views
Recommends
on
Amazon AuroraAmazon Aurora

Hi Erin! First of all, you'd probably want to go with a managed service. Don't spin up your own MySQL installation on your own Linux box. If you are on AWS, thet have different offerings for database services. Standard RDS vs. Aurora. Aurora would be my preferred choice given the benefits it offers, storage optimizations it comes with... etc. Such managed services easily allow you to apply new security patches and upgrades, set up backups, replication... etc. Doing this on your own would either be risky, inefficient, or you might just give up. As far as which database to chose, you'll have the choice between Postgresql, MySQL, Maria DB, SQL Server... etc. I personally would recommend MySQL (latest version available), as the official tooling for it (MySQL Workbench) is great, stable, and moreover free. Other database services exist, I'd recommend you also explore Dynamo DB.

Regardless, you'd certainly only keep high-level records, meta data in Database, and the actual files, most-likely in S3, so that you can keep all options open in terms of what you'll do with them.

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Recommends
on
PostgreSQLPostgreSQL

Hi Erin,

  • Coming from "Big" DB engines, such as Oracle or MSSQL, go for PostgreSQL. You'll get all the features you need with PostgreSQL.
  • Your case seems to point to a "NoSQL" or Document Database use case. Since you get covered on this with PostgreSQL which achieves excellent performances on JSON based objects, this is a second reason to choose PostgreSQL. MongoDB might be an excellent option as well if you need "sharding" and excellent map-reduce mechanisms for very massive data sets. You really should investigate the NoSQL option for your use case.
  • Starting with AWS Aurora is an excellent advise. since "vendor lock-in" is limited, but I did not check for JSON based object / NoSQL features.
  • If you stick to Linux server, the PostgreSQL or MySQL provided with your distribution are straightforward to install (i.e. apt install postgresql). For PostgreSQL, make sure you're comfortable with the pg_hba.conf, especially for IP restrictions & accesses.

Regards,

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Klaus Nji
Staff Software Engineer at SailPoint Technologies · | 1 upvotes · 450K views
Recommends
on
PostgreSQLPostgreSQL

I recommend Postgres as well. Superior performance overall and a more robust architecture.

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Pros of Azure Cosmos DB
Pros of Microsoft SQL Server
  • 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
  • 139
    Reliable and easy to use
  • 101
    High performance
  • 95
    Great with .net
  • 65
    Works well with .net
  • 56
    Easy to maintain
  • 21
    Azure support
  • 17
    Full Index Support
  • 17
    Always on
  • 10
    Enterprise manager is fantastic
  • 9
    In-Memory OLTP Engine
  • 2
    Security is forefront
  • 2
    Easy to setup and configure
  • 1
    Docker Delivery
  • 1
    Columnstore indexes
  • 1
    Great documentation
  • 1
    Faster Than Oracle
  • 1
    Decent management tools

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Cons of Azure Cosmos DB
Cons of Microsoft SQL Server
  • 18
    Pricing
  • 4
    Poor No SQL query support
  • 4
    Expensive Licensing
  • 2
    Microsoft

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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 Microsoft SQL Server?

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

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

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What are some alternatives to Azure Cosmos DB and Microsoft SQL Server?
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