AWS CSA
  • Introduction
  • 1. AWS Overview
    • 1.1 AWS global Infrastructure
    • 1.2 Networking and Content Delivery
    • 1.3 Computing
    • 1.4 Storage
    • 1.5 Databases
    • 1.6 Migration Services
    • 1.7 Analytics
    • 1.8 Security and Identity
    • 1.9 Management Tools
    • 1.10 Application Services
    • 1.11 Developer Tools
    • 1.12 Mobile Services
    • 1.13 Desktop and App Streaming
    • 1.14 Artificial Intelligence
    • 1.15 Messaging
  • 2. IAM - Identity Access Management
    • 2.1 IAM Introduction
    • 2.2 IAM Labs
    • 2.3 Create a billing alart
    • 2.4 IAM Conclusion
  • 3. S3 - Simple Storage Service
    • 3.1 S3 Introduction
    • 3.2 S3 Labs
    • 3.3 Version Control Labs
    • 3.4 Cross Region Replication
    • 3.5 Life Cycle Management
    • 3.6 CloudFront
    • 3.7 CloudFront Labs
    • 3.8 S3 Security and Encryption
    • 3.9 Storage Gateway
    • 3.10 Snowball
    • 3.11 Snowball Labs
    • 3.12 S3 Transfer Acceleration
    • 3.13 Create a static web page using S3
    • 3.14 Storage Summary
  • 4. EC2 - Elastic Compute Cloud
    • 4.1 EC2 Introduction I
    • 4.2 EC2 Introduction II
    • 4.3 EC2 Lab 1
    • 4.4 EC2 Lab 2
    • 4.5 Security Groups Lab
    • 4.6 Upgrade EBS Volume Types - Lab1
    • 4.7 Upgrade EBS Volume Types - Lab2
    • 4.8 RAID, Volumes & Snapshots
    • 4.9 Create An AMI - Lab
    • 4.10 AMI's EBS Root Volumes vs. Instance Store
    • 4.11 Elastic Load Balancer & Health Check - Lab
    • 4.12 CloudWatch EC2 - Lab
    • 4.13 The AWS Command Line & EC2
    • 4.14 Using IAM Roles with EC2
    • 4.15 S3 CLI & Regions
    • 4.16 Using Bootstrap Scripts
    • 4.17 EC2 Instance Metadata
    • 4.18 Launch Configurations & Auto Scaling Groups
    • 4.19 EC2 Placement Groups - Exam Must Know
    • 4.20 Elastic File System (EFS) Lab
    • 4.21 Lambda Concepts
    • 4.22 Build A Serverless Webpage Using API Gateway & Lambda
    • 4.23 Use Polly to Pass Your Exam - Lab of a Serverless Application
    • 4.24 Use Polly to Pass Your Exam - Lab of a Serverless Application
    • 4.25 EC2 - Summary & Exam Tips
  • 5. Route53
    • 5.1 DNS 101
    • 5.2 Route53 - Register A Domain Name - Lab
    • 5.3 Setup Our EC2 Instances - Lab
    • 5.4 Routing Policies - Lab
  • 6. Databases on AWS
    • 6.1 Databases 101
    • 6.2 Launching an RDS Instance - Lab
    • 6.3 RDS - Backups, Multi-AZ & Read Replicas
    • 6.4 DynamoDB
    • 6.5 Redshift
    • 6.6 ElastiCache
    • 6.7 Aurora
    • 6.8 Database Summary
  • 7. VPC
    • 7.1 VPC Overview
    • 7.2 VPC Lab - Part 1
    • 7.3 VPC Lab - Part 2
    • 7.4 NAT Instances & NAT Gateways
    • 7.5 Network Access Control Lists vs. Security Groups
    • 7.6 Load Balancers & Custom VPCs
    • 7.7 VPC Flow Logs
    • 7.8 NATs vs. Bastions
    • 7.9 VPC End Points
    • 7.10 VPC Clean Up
    • 7.11 VPC Summary
  • 8. Application Services
    • 8.1 SQS - Simple Queue Service
    • 8.2 SWF - Simple Workflow Service
    • 8.3 SNS - Simple Notification Service
    • 8.4 Elastic Transcoder
    • 8.5 API Gateway
    • 8.6 Kinesis 101
    • 8.7 Kinesis Streams Lab
    • 8.8 Application Services Summary
  • 9. White Paper Reviews
    • 9.1 Overview of AWS
    • 9.2 Overview of Security Processes - Part 1
    • 9.3 Overview of Security Processes - Part 2
    • 9.4 Risk & Compliance Whitepaper
    • 9.5 Storage Options in the Cloud Whitepaper
    • 9.6 Architecting For The Cloud Best Practices Whitepaper
  • 10. Well Architected Framework
    • 10.1 Introduction of Well Architected Framework
    • 10.2 Pillar One - Security
    • 10.3 Pillar Two - Reliability
    • 10.4 Pillar Three - Performance
    • 10.5 Pillar Four - Cost Optimization
    • 10.6 Pillar Five - Operational Excellence
    • 10.7 Well Architected Framework - Summary
  • 11. Additional Exam Tips
    • 11.1 Exam Tips Based On Student Feedback
    • 11.2 Consolidated Billing
    • 11.3 AWS Organizations - Lab
    • 11.4 Cross Accounts Access
    • 11.5 Resource Groups & Tagging
    • 11.6 VPC Peering & ClassicLink
    • 11.7 Direct Connect
    • 11.8 Security Token Service
    • 11.9 Active Directory Integration
    • 11.10 Workspaces
    • 11.11 ECS - Part 1 - What is Docker
    • 11.12 ECS - Part 2 - What is ECS
    • 11.13 CloudFormation - A Brief Introduction
    • 11.14 Step Functions - A Brief Introduction
  • 12. Practice Tests Questions Summary
    • 12.1 Whizlabs - Free Test
    • 12.2 Whizlabs - Diagnosis Test
    • 12.3 Whizlabs - Practice Test I
    • 12.4 Whizlabs - Practice Test II
    • 12.5 Whizlabs - Practice Test III
    • 12.6 Whizlabs - Practice Test IV
    • 12.7 Whizlabs - Practice Test V
    • 12.8 Whizlabs - Practice Test VI
    • 12.9 Whizlabs - Practice Test VII
    • 12.10 Whizlabs - Section Tests - Part 1
    • 12.11 Whizlabs - Section Tests - Part 2
    • 12.12 Udemy - Final Quiz
  • 13. The Real World - Creating a fault tolerant Word Press Site
    • 13.1 Getting Setup
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On this page
  • AWS Database Services
  • Relational database
  • Non-relational databases
  • Data warehouse
  • OLTP vs. OLAP
  • In-memory database/cache
  • DMS (Database Migration Service)

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  1. 6. Databases on AWS

6.1 Databases 101

AWS Database Services

  • RDS (Relational database)

  • DynamoDB (NoSQL database)

  • ElastiCache (In-memory database)

  • Redshift (Data warehouse)

  • DMS (Database migration service)

Relational database

Relational databases are what most of us are all used to. They have been around since the 70's. Think of a traditional spreadsheet.

  • Database

  • Tables

  • Row

  • Fields (Columns)

Six databases available on AWS RDS (Relational Database Service)

  • SQL Server

  • Oracle

  • MySQL Server

  • PostgreSQL

  • Aurora

  • MariaDB

Non-relational databases

DynamoDB database:

  • Collection = Table

  • Document (like object data type in JavaScript) = Row

  • Key-value pairs (value can be any data type) = Fields

DynamoDB is document-oriented (like MongoDB) and it also supports key-value data model. Document database is essentially a key-value database with more features.

Data warehouse

Used for business intelligence. Tools like Cognos, Jaspersoft, SQL Server Reporting Services, Oracle Hyperion, SAP NetWeaver.

Used to pull in very large and complex data sets. Usually used by management to do queries on data (such as current performance vs targets etc).

OLTP vs. OLAP

OLTP - Relational database.

OLAP - Data warehouse.

Online Transaction Processing (OLTP) differs from Online Analytics Processing (OLAP) in terms of the types of queries run.

#1. OLTP Example:

Order number 2120121

Pulls up a row of data such as Name, Date, Address to Deliver to, Delivery Status etc.

#2. OLAP transection Example:

Net Profit for EMEA and Pacific for the Digital Radio Product.

Pulls in large numbers of records: ...

You can imagine the amount of data that's going to be involved in this sort of transaction. It will be huge and it is going to hit the database really hard with lots of different queries and it is going to have a big effect on the database. Now with relational databases traditionally they're very difficult to scale out. You need to have a production database and if you are running these queries on your production database and also trying to do online transaction processing which allows your customers to pay new orders, it is going to hurt the database and it is going to really effect the IO. So data warehouse has come into existence where you more or less have a copy of your production database and this copy of the database is where you are going to run your OLAP transactions on.

Data warehousing databases use different type of architecture both from a database perspective and infrastructure layer.

In-memory database/cache

ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower dist-based databases. ElastiCache supports two open-source in-memory caching engines:

  • Memcached

  • Redis

ElastiCache is cool because it can cache the most consistently queried aspects of your database. So if your web application is constantly requesting what the top 10 deals for today you might want to cache that information in an ElastiCache and in that way when your web application handle the query for the top 10 deals it is going to get from ElastiCache and it is not going to get that from you database. It just takes a load off your database and allows you to improve the performance of your underlining database.

DMS (Database Migration Service)

DMS allows you to migrate your production database to AWS. Once the migration has started, AWS manages all the complexities of the migration process like data type transformation, compression, and parallel transfer (for faster data transfer) while ensuring that data changes to the source database that occur during the migration process are automatically replicated to the target.

AWS schema conversion tool automatically converts the source database schema and a majority of the custom code, including views, stored procedures, and functions, to a format compatible with the target database.

Previous6. Databases on AWSNext6.2 Launching an RDS Instance - Lab

Last updated 5 years ago

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