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Amazon RDS vs Azure SQL Database: What are the differences?

Introduction

In this article, we will compare Amazon RDS and Azure SQL Database, two popular cloud-based relational database services. We will focus on their key differences to help you understand which one might be more suitable for your specific needs.

  1. Scalability: Amazon RDS provides automatic scaling capabilities, allowing you to easily adjust your database resources as needed. It offers features like read replicas and Multi-AZ deployments for high availability. Azure SQL Database also offers scalability options, but it has a more granular approach with Elastic Pools, which allows you to share resources among multiple databases, and Hyperscale for handling large data volumes efficiently.

  2. Pricing: Amazon RDS follows a pay-as-you-go pricing model, where you are billed based on the usage of database instances and storage resources. Additional costs may apply for features like Multi-AZ deployments and read replicas. On the other hand, Azure SQL Database offers different pricing tiers based on performance levels, storage size, and additional features like geo-replication. It also provides reserved capacity options for cost optimization.

  3. Platform Support: Amazon RDS supports a wide range of database engines such as MySQL, PostgreSQL, Oracle, and SQL Server. It provides managed services for these engines, taking care of administrative tasks like patching and backups. Azure SQL Database is specifically designed for Microsoft SQL Server workloads, offering a fully managed service with various compatibility levels for better migration options.

  4. Integration with Cloud Ecosystem: Amazon RDS is part of the broader AWS ecosystem, allowing seamless integration with other services like Amazon S3 for backups and Amazon CloudWatch for monitoring. It also provides integration with AWS Identity and Access Management (IAM) for access control. Azure SQL Database is tightly integrated with the Azure platform, enabling integration with services like Azure Storage for backups and Azure Monitor for monitoring and performance insights. It also leverages Azure Active Directory for access management.

  5. High Availability and Disaster Recovery: Amazon RDS offers Multi-AZ deployments, where synchronous standby replicas are created in different availability zones for high availability. It also supports automated backups and point-in-time recovery. Azure SQL Database provides built-in high availability with automatic failover between replicas, ensuring business continuity. It also offers geo-replication for disaster recovery purposes.

  6. Developer Tools and Ecosystem: Amazon RDS benefits from the extensive AWS ecosystem, providing a wide range of developer tools, SDKs, and APIs for seamless application development and management. It also supports AWS Database Migration Service for easy database migrations. Azure SQL Database benefits from the Microsoft ecosystem, offering various developer tools like SQL Server Management Studio (SSMS), Azure Data Studio, and Visual Studio for database administration and development. It provides Azure Database Migration Service for simplified migrations.

In Summary, Amazon RDS and Azure SQL Database differ in scalability options, pricing models, platform support, integration with cloud ecosystem, high availability and disaster recovery features, and developer tools and ecosystem. Choose Amazon RDS for its flexibility across multiple database engines and strong integration with AWS services, while Azure SQL Database is more suitable for Microsoft SQL Server workloads with its tight integration with the Azure platform.

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Pros of Amazon RDS
Pros of Azure SQL Database
  • 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
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable

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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 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 Amazon RDS?
What companies use Azure SQL Database?
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What are some alternatives to Amazon RDS and Azure SQL Database?
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