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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon RDS vs Azure SQL Database

Amazon RDS vs Azure SQL Database

OverviewComparisonAlternatives

Overview

Amazon RDS
Amazon RDS
Stacks16.2K
Followers10.8K
Votes761
Azure SQL Database
Azure SQL Database
Stacks585
Followers502
Votes13

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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Detailed Comparison

Amazon RDS
Amazon RDS
Azure SQL Database
Azure SQL Database

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.

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.

Pre-configured Parameters;Monitoring and Metrics;Automatic Software Patching;Automated Backups;DB Snapshots;DB Event Notifications;Multi-Availability Zone (Multi-AZ) Deployments;Provisioned IOPS;Push-Button Scaling;Automatic Host Replacement;Replication;Isolation and Security
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Statistics
Stacks
16.2K
Stacks
585
Followers
10.8K
Followers
502
Votes
761
Votes
13
Pros & Cons
Pros
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
Pros
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable

What are some alternatives to Amazon RDS, Azure SQL Database?

MongoDB

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.

MySQL

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.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

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

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

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.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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