Relational Database in AWS Using Amazon RDS
How would you like to store, manage, and secure your relational database all from one easy-to-use online service? Amazon RDS allows you to do just that.
Using Amazon RDS, you can set up, operate, and scale a relational database service in the cloud with just a few clicks in the AWS Management Console or using simple APIs and CLI tools.
You can then use your custom applications or popular third-party applications such as Microsoft SQL Server and Oracle to access these data using the features and performance of commercial databases without having to purchase, install, or manage any software or hardware yourself.
MySQL
The standard MySQL service is built for your production database needs, with 24 x 7 support and enhanced availability options to provide redundancy and fault tolerance. With MySQL, you can have a failover solution without incurring any data loss and without having to implement complicated time-consuming replication schemes.
Because of its high availability, you can rely on MySQL Service not only as a production database but also as a migration path for new applications that require disaster recovery support.
You can also scale up or down using managed instance groups while monitoring resources to ensure optimal performance at all times.
You can easily create read replicas of your production databases to get the benefits of geographic distribution or use it as a development sandbox for testing patches before applying them to the original environment.
Amazon Aurora
With a simple and fast web service, you can set up Amazon Aurora with only two steps. After completing these two steps, you can use it as if it were any other relational database.
You can create tables using SQL (the language of most relational databases) to store any kind of data for your applications or websites.
You can also change any setting through SQL at any time without having to take your website down. If you know SQL, then you can customize the configurations that suit your needs.
Aurora is available in both MySQL and PostgreSQL engines that offer consistent performance on every workload including high-volume transactional workloads, scale-out read workloads, and mixed workloads with both reads and write.
You can easily migrate existing MySQL or PostgreSQL databases to Amazon Aurora without taking them offline.
MariaDB
Amazon RDS supports multiple versions of MariaDB. To get started, see Getting Started with MariaDB on Amazon RDS.
You can also use MySQL and PostgreSQL to build your application using some or all of your data stored on those databases.
For more information, see Which Databases Are Available on AWS? and Building a Serverless Application with DynamoDB, API Gateway, Lambda, and MongoDB.
The Amazon Aurora Serverless database is compatible with Python. You can get started by reading Introduction to the Serverless Aurora MySQL RDS-based DBMS for Developers for more information about how you can use this database for your applications.
It’s important to note that MySQL does not support transactions. It does, however, offer dynamic programming such as triggers, functions, events, and views that may be valuable for developing certain types of applications.
If you’re new to relational databases, it’s worth noting that most of them require setting up user accounts (either locally or through a cloud service).
When creating these accounts there are several points to consider including what permissions the account should have and where it should be created from.
PostgreSQL
Amazon RDS supports PostgreSQL databases, a powerful open-source object-relational database system.
With PostgreSQL, you can get started quickly with built-in functionality such as triggers and foreign keys that make managing data easier.
Developers also benefit from built-in features such as full-text search and replication to enhance database availability.
The PostgreSQL database engine uses a shared nothing architecture where each node is separate and independently scalable.
In addition, since you can use Amazon RDS DB instances with other products (for example, DynamoDB or Elastic MapReduce), it’s easy to combine multiple services into your application stack.
You can set up failover protection for your DB instance by replicating it to one or more standby instances, ensuring high availability and scalability for your applications.
If a DB instance becomes unavailable, the most recent replica will automatically promote itself to be the new primary and serve read/write requests.
To minimize downtime during this process, the original primary typically promotes its next available replica within seconds of becoming unavailable.
The following are some of the notable benefits of using PostgreSQL on Amazon RDS:
A) Built-in row level locking for greater concurrency
B) Strong consistency across an active multi-master topology
C) Read scaling through cluster sharing between reading replicas
D) Highly tunable memory settings
Oracle
The second largest database service available in AWS is Oracle. This database is known for being able to handle massive amounts of data.
The read replicas make it easy to scale, too. If you’re looking for a top-notch relational database, Oracle could be a great fit.
Many companies like using Oracle when they want to use features such as point-in-time recovery and partitioning—both of which are available as part of its implementation on AWS with Amazon RDS (Relational Database Service).
However, because Oracle offers so many services related to the storage of data, you need additional expertise if your team doesn’t already have them on staff.
Additionally, there can be some drawbacks to using this particular database. For example, replication may not work well across availability zones, and backups are limited by size.
It’s important to keep these considerations in mind before selecting this database.
Microsoft SQL Server
SQL Server is a Microsoft relational database management system that offers easy-to-use SQL development.
It is a powerful, scalable database that can handle large amounts of data with high availability and security for server workloads.
SQL Server is best suited for line-of-business applications. It has a low learning curve and requires no maintenance or tuning on the customer’s part.
However, it is not available as an EC2 instance type. You must provision an Amazon RDS DB instance type before you can create an instance from this AMI.
The standard configuration for MS SQL Server Standard instances includes two vCPUs and 15 GB of memory (with configurable upgrades) at no additional charge to provide flexibility for heavy read or write workloads or systems requiring more resources.
The storage requirements are 10GB per 1TB of user databases stored on the instance; however, you are allowed to allocate up to 100% reserved storage capacity using either General Purpose SSD (GP2) or Provisioned IOPS SSD (IO1).
