Amazon Web Service is increasingly developing and supporting many great features. Today we will learn the basics of Amazon Relational Database Service (RDS).
I. What is Database?
Database is a word commonly used in the fields of information technology, data, programming and software … .Database is a database, a collection of data organized and often displayed. accessed from a computer system or exists as a file in the database administration system. It allows an application to save, manage and retrieve data quickly
Relation Database is a relational database containing at least one table that you can visualize as a spreadsheet with columns and rows. In a relational database table, columns can also be called properties, and rows can also be called records or tuples. There are 2 types of Relation Database :
Online Transaction Processing (OLTP) : OLTP database is suitable for applications that read and write data frequently, in order of many times per second. They are optimized for fast queries, and those queries tend to be frequent and predictable. Depending on the size of the database and its required performance, an OLTP database may have high memory requirements so that it can store frequently accessed parts of the table in memory to fast access. In general, a server has ample memory and computational power handling all writes to an OLTP database. OLTP database will be a good candidate to support an online ordering system that specializes in processing hundreds of orders per minute.
Online Analytic Processing : OLAP database is optimized for complex queries based on large data sets so it OLAP database tends to require heavy computation and storage. In an application data warehouse, it is common practice to aggregate multiple OLTP databases into a single OLAP database. For example, in an OLTP database for an employee management system, employee data can be spread across multiple tables. At regular but infrequent intervals, a data warehouse consolidates these tables into a single table in the OLAP database. This makes it easier to write queries based on data and reduces the amount of time required to process such a query. With large OLAP databases, it is common for multiple database servers to share computational volumes of complex queries. In a process called partitioning, each server receives a portion of the database for which it is responsible.
II. Relation Database Service
Amazon Relational Database Service (RDS) is a managed database service that allows you to run a relational database system in the cloud. RDS is responsible for setting up the system database, performing backups, ensuring high availability, and patching the underlying operating system and database software. RDS also makes it easy to recover from faulty databases, recover data, and scale your database to achieve the level of performance and utilization your application requires. To deploy a database using RDS, you start by configuring a database instance, which is an isolated database environment. A database instance exists in a virtual private cloud (VPC) that you specify, but unlike the EC2 version, AWS fully manages the database instances. You cannot SSH into them and they are not visible in your EC2 versions. To use Amazon RDS, we need to know a few points:
Database engine is simply software that stores, organizes and retrieves data in a database. Each database instance runs only one database engine. RDS offers the following six database tools to choose from:
- Mysql : MySQL is designed for OLTP applications like blogging and e-commerce. RDS offers the latest versions of MySQL Community Edition, including 5.5, 5.6 and 5.7. MySQL provides two storage engines – MyISAM and InnoDB – but you should use the following tool as it is the only one compatible with automatic backups managed by RDS.
- MariaDB : MariaDB is a drop-in binary alternative to MySQL. It was created over concerns about MySQL’s future after Oracle acquired the company that developed it. RDS provides multiple versions of MariaDB, from 10.0.17 to 10.2. MariaDB supports the XtraDB and InnoDB storage engines, but AWS recommends the following for maximum parent compatibility with RDS
- Oracle : Oracle is one of the most widely deployed relational database management systems. Some applications explicitly require an Oracle database.
- PostgreSQL : Self-advertised PostgreSQL is the most open source Oracle compatible database. This is a good option when you have in-house applications that have been developed for Oracle but want to keep costs down. RDS offers versions of PostgreSQL from 9.3.12-R1 to 10.4-R1.
- Amazon Aurora : Aurora is Amazon’s drop-in binary alternative to MySQL and PostgreSQL. Aurora provides better recording performance than both by using a virtualized stor age class that reduces write times to underlying storage. Depending on which version you choose, Aurora is PostgreSQL-compatible or MySQL-compatible for importing and exporting tools and snapshots. Aurora is designed to allow you to seamlessly migrate from an existing deployment that uses either of those open source databases. For MySQL-Compatible Versions, Aurora only supports InnoDB host engine. In addition, the Aurora Backtrack for MySQL Feature allows you, within seconds, to restore the database to any point in the last 72 hours.
- Microsoft SQL Server : RDS offers multiple editions of Microsoft SQL Server: 2008 R2, 2012, 2014, 2016, and 2017. For editions, you can choose from Express, Web, Standard, and Enterprise. Variety of flavors makes it possible to migrate an existing SQL Server database from on-premises deployment to RDS without having to perform any database upgrades.
Database Instance Classes When launching a database instance, you have to decide how much processing power, memory, network bandwidth and disk throughput it needs. RDS provides a variety of database instance classes to meet the diverse performance needs of different databases. If you get it wrong or if your needs change, you can move your instance to another class. RDS divides database instance classes into the following three categories:
- Standard : The standard meets the needs of most databases. The latest generation class version is db.m4, providing the maximum: 256 GB memory, 64 vCPU, 25 Gbps network bandwidth, 10,000 Mbps (1,280 MBps) disk throughput
- Memory Optimized : for high performance databases. Providing more memory for the database allows it to store more data in memory, which can lead to faster query times. The latest generation version is db.x1e and it provides up to: 3,904 GB memory, 128 vCPU, 25 Gbps network bandwidth, 14,000 Mbps (1,750 MBps) disk throughput.
- Burst Capable (Burstable) : for development, testing and other non-production databases. The only explosive instance class available is db.t2 and it gives you maximum: 32 GB memory, 8v CPU.
Storage Choosing the correct memory for your version of the database is more than just making sure you have enough disk space. You must also decide whether the storage speed should meet the performance requirements of the applications supported by your database. There are 3 types of storage:
- General-Purpose SSD : provides cost-effective storage, ideal for a wide range of workloads. These volumes provide one-digit millisecond latency and the ability to spike to 3,000 IOPS in the long run. The base performance for these drives is determined by the size of the drive.
- Provisioned IOPS : designed to meet the needs of I / O-intensive workloads, especially database workloads, low I / O latency requirements and the most I / O throughput shop.
- Magnetic : Amazon RDS also supports magnetic storage for backward compatibility. We recommend using the General Purpose SSD or the provided IOPS for any new storage needs. The maximum amount of memory allowed for DB instances on magnetic memory is less than for other types of memory
Above are some basic knowledge you need to know before using Amazon Relation Database Service (RDS). Hope it will help you guys.
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html