Amazon Database note

 MySQL, PostgreSQL, Oracle, Microsoft SQL Server,

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//  Lift-and-Shift

migrate db environtment onprem to cloud

This means you have control over the same variables you do, in your on-premises environment, such as OS, memory, CPU, storage capacity, and so forth.

++ DATABASE MIGRATION SERVICE 

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// amazon RDS

running your databases in the cloud is to use a more managed service called Amazon Relational Database Service, or RDS

Amazon Relational Database Service (Amazon RDS)(opens in a new tab) 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).

// amazon RDS support

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

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// amazon aurora

support mysql

support postgresql

- price 1/10 cost of commercial db

ada data replication & 6 copy at a time

bs apply 15 read replicas. // offload read and scale performance 

ada continuous backup to s3 ,, ready to restore 

ada point in time recovery : can recover data from specific period

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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.

ID Product name Size Price

1 Medium roast ground coffee 12 oz. $5.30

2 Dark roast ground coffee 20 oz. $9.27

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// Amazon DynamoDB

- serverless database

table -> 

data organize into item.

item -> attributes

- redundant across AZ

- high performance / ms response time 

- support million of user

- noSQL database

- non relational database

- non schema

- add or remove attribute in table 

- simpler. fast.

- quick in response time and high scalable 

- fully managed

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Nonrelational databases are sometimes referred to as “NoSQL databases” because they use structures other than rows and columns to organize data. One type of structural approach for nonrelational databases is key-value pairs. With key-value pairs, data is organized into items (keys), and items have attributes (values). You can think of attributes as being different features of your data.

In a key-value database, you can add or remove attributes from items in the table at any time. Additionally, not every item in the table has to have the same attributes. 

Key Value

1

Name: John Doe

Address: 123 Any Street

Favorite drink: Medium latte

2

Name: Mary Major

Address: 100 Main Street

Birthday: July 5, 1994

Amazon DynamoDB(opens in a new tab) is a key-value database service. It delivers single-digit millisecond performance at any scale.

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// rds vs dynamoDb

AWS Cloud Practitioners, welcome back to the championship chase of the database! In the relational corner, engineered to remove undifferentiated heavy lifting from your database administrators with automatic high availability and recovery provided. You control the data, you control the schema, you control the network. You are running Amazon RDS. Yes, Yeah. 

The NoSQL corner, using a key value pair that requires no advanced schema, able to operate as a global database at the touch of a button. It has massive throughput. It has petabyte scale potential. It has granular API access. It is Amazon DynamoDB. 

rds: business analytic.

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// amazon redshift

Amazon Redshift(opens in a new tab) is a data warehousing service that you can use for big data analytics. It offers the ability to collect data from many sources and helps you to understand relationships and trends across your data.

data warehouse => buat big data.

historical analytic opposed to operational analysis.

- data warehouse as a service

-  multiple petabyte size 

- 10 times higher performance than relational db

// amazon redshift spectrum 

- run single sql query against exabytes of unstructured data running in data lakes.

Amazon Redshiftis a data warehousing service that you can use for big data analytics. It offers the ability to collect data from many sources and helps you to understand relationships and trends across your data.

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// AWS Database Migration Service (AWS DMS)

migrate existing db between source and target.

source tetep operational pas dipindah

downtime is minimized for app that rely on that database

source and target db ga perlu type yg sama 

mysql - amazon RDS

microsoft sql - amazon RDS

oracle - amazon RDS for oracle 

// compatible database

schema structure 

data type

database code

on premise ec2, amazon rds ------  cloud ec2, amazon rds

// heterogonous database

source dand destination berbeda databasenya.

mesti 2 step process. convert dl pake

AWS Schema Convertion Tool.

// 2 ini ke convert pake aws schema convertion tool

schme structure + 

data type -

database code  +

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// 3 kegunaan lain DMS:

- development and test database migration  // migrate or copy data to 2nd db

- database consolidation  // gabungin beberapa db menjadi 1 

- continuous database replication   // continous db replication in multiple place

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// summary

dynamoDB : great for key value pair  

// amazon DocumentDB  ( with MongoDB Compatibility )

- great for small attributes

contoh: full content management system, catalog, user profile, 

// amazon Neptune

social web media tracking

fraud detection

supply chain. // track assurance that nothing is lost 

// amazon Managed Blockchain

blockchain solution 

- decentralization components.

// amazon Quantum Ledger Database  ( QLDB )

immutable ledger.  any entry can never be removed from audits.

// amazon ElastiCache 

- database accelerators.

bs dikasih caching layer. improve from milisecond to microseconds

ga perlu launch, uplift, maintenance.

comes with both memcached and redis flavors

// amazon DynamoDB Accelerator ( DAX )

- database accelrator for DynamoDB

improving read times for non relational data

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best for archival data:

Amazon S3 Glacier Flexible Retrieval

Amazon S3 Glacier Deep Archive

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