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Amazon RDS vs Microsoft SQL Server: What are the differences?

Introduction

Amazon RDS (Relational Database Service) and Microsoft SQL Server are both widely used database management systems (DBMS) that offer various features and capabilities. However, there are key differences between the two that distinguish them from each other. In this article, we will explore and highlight these differences to provide a clearer understanding of their unique offerings.

  1. Deployment and Management: Amazon RDS is a managed service that takes care of essential database administration tasks such as backups, software patching, and hardware provisioning, allowing users to focus more on their applications. In contrast, Microsoft SQL Server requires users to handle these management aspects themselves, providing more control but also more responsibility.

  2. Scalability Options: Amazon RDS offers multiple scalability options, such as vertical scaling (increasing server size) and horizontal scaling (replicating databases to multiple instances). Microsoft SQL Server also supports scaling vertically, but horizontal scaling requires additional configuration and setup, making it a more complex process compared to Amazon RDS.

  3. Availability and Fault Tolerance: Amazon RDS provides built-in features like automated backups, database snapshots, and Multi-AZ deployment, which ensures high availability and fault tolerance. On the other hand, Microsoft SQL Server requires manual configuration and setup for achieving similar levels of availability and fault tolerance, making it more time-consuming and potentially prone to errors.

  4. Integration with Cloud Services: Amazon RDS seamlessly integrates with other Amazon Web Services (AWS) offerings, allowing easy integration with services like Amazon S3, Amazon CloudWatch, and AWS Identity and Access Management (IAM). Microsoft SQL Server offers integration with Azure services, but the level of integration may not be as comprehensive or tightly integrated as with Amazon RDS and AWS services.

  5. Database Portability: Amazon RDS allows users to easily migrate their databases across different database engines supported by RDS, such as MySQL, PostgreSQL, Oracle, and SQL Server itself. Microsoft SQL Server, while providing tools for migration, does not offer the same level of flexibility and ease when it comes to migrating between different database engines.

  6. Licensing and Costs: Amazon RDS offers a variety of licensing options for different database engines, including options for bringing your own licenses (BYOL), which can potentially lower the overall costs. Microsoft SQL Server, on the other hand, follows its own licensing model, which may have different cost implications and may require separate license purchases when used with certain cloud or hosting providers.

In Summary, Amazon RDS simplifies deployment and management, offers flexible scalability options, provides built-in availability features, extensive integration with cloud services, supports easy database portability, and provides different licensing options, making it a viable choice for many organizations. However, Microsoft SQL Server provides more control over management, scalability, and customization, but also requires a greater level of manual configuration and setup.

Advice on Amazon RDS 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
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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 · 510.2K views
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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 · 509.8K views
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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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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 · 509.9K views
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PostgreSQLPostgreSQL

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

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Pros of Amazon RDS
Pros of Microsoft SQL Server
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
  • 30
    Control iops, fast restore to point of time
  • 28
    Security
  • 24
    Elastic
  • 20
    Push-button scaling
  • 20
    Automatic software patching
  • 4
    Replication
  • 3
    Reliable
  • 2
    Isolation
  • 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
    Always on
  • 17
    Full Index Support
  • 10
    Enterprise manager is fantastic
  • 9
    In-Memory OLTP Engine
  • 2
    Easy to setup and configure
  • 2
    Security is forefront
  • 1
    Great documentation
  • 1
    Faster Than Oracle
  • 1
    Columnstore indexes
  • 1
    Decent management tools
  • 1
    Docker Delivery
  • 1
    Max numar of connection is 14000

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Cons of Amazon RDS
Cons of Microsoft SQL Server
    Be the first to leave a con
    • 4
      Expensive Licensing
    • 2
      Microsoft
    • 1
      Data pages is only 8k
    • 1
      Allwayon can loose data in asycronious mode
    • 1
      Replication can loose the data
    • 1
      The maximum number of connections is only 14000 connect

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    What is Amazon RDS?

    Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

    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 are some alternatives to Amazon RDS and Microsoft SQL Server?
    Amazon Redshift
    It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
    Apache Aurora
    Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
    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.
    Oracle
    Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
    Heroku Postgres
    Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
    See all alternatives