[Storage and Databases] Amazon Relational Database Service (Amazon RDS)

Relational databases

In a relational database, data is stored in a way that relates it to other pieces of data. 

An example of a relational database might be the coffee shop’s inventory management system. Each record in the database would include data for a single item, such as product name, size, price, and so on.

 

Relational databases use structured query language (SQL) to store and query data. This approach allows data to be stored in an easily understandable, consistent, and scalable way. For example, the coffee shop owners can write a SQL query to identify all the customers whose most frequently purchased drink is a medium latte.

Example of data in a relational database:

ID          Product name                                                                                 Size            Price

1	Medium roast ground coffee	12 oz.	$5.30
2	Dark roast ground coffee	20 oz.	$9.27

Lift and Shift Migration

- Upload it to database easily

- OS and Memory Capacity, etc

 

Amazon Relational Database Service

Amazon Relational Database Service (Amazon RDS) is a service that enables you to run relational databases in the AWS Cloud.

Amazon RDS is a managed service that automates tasks such as hardware provisioning, database setup, patching, and backups. With these capabilities, you can spend less time completing administrative tasks and more time using data to innovate your applications. You can integrate Amazon RDS with other services to fulfill your business and operational needs, such as using AWS Lambda to query your database from a serverless application.

Amazon RDS provides a number of different security options. Many Amazon RDS database engines offer encryption at rest (protecting data while it is stored) and encryption in transit (protecting data while it is being sent and received).

• Automated patching
• Backups
• Redundancy
• Failover
• Disaster recovery

 

Amazon RDS database engines

Amazon RDS is available on six database engines, which optimize for memory, performance, or input/output (I/O). Supported database engines include:

• Amazon Aurora
• PostgreSQL
• MySQL
• MariaDB
• Oracle Database
• Microsoft SQL Server

 

Amazon Aurora

Amazon Aurora is an enterprise-class relational database. It is compatible with MySQL and PostgreSQL relational databases. It is up to five times faster than standard MySQL databases and up to three times faster than standard PostgreSQL databases.

Amazon Aurora helps to reduce your database costs by reducing unnecessary input/output (I/O) operations, while ensuring that your database resources remain reliable and available. 

Consider Amazon Aurora if your workloads require high availability. It replicates six copies of your data across three Availability Zones and continuously backs up your data to Amazon S3.

 

- 1/10th the cost of commercial databases

- Data replication (6 copy basic)

- Up to 15 replicas

- Continous back up to Amazon S3

- Post-in Time Memory