Databases Flashcards

1
Q

Databased

A

Structured
Enables efficiency with query and searching through the data

Defined relationships

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2
Q

Relational Database

A

Like excel spreadsheets.

Links between them

Can use SQL to perform queries or lookups

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3
Q

NoSQL databases

A

Non relational databases.

Built for specific purpose with specific data model in mind.

Flexible Schema / Shape.

Benefit is flexibility. Easy to make it evolve.

Scalable with distributed servers.

High performance

Highly functional

Examples:

Key- Value

Graph Database

In-memory

Search databases

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4
Q

NoSQL- data example

A

JSON format

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5
Q

JSON

A

JavaScript Object Notation

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6
Q

JSON

A

Common way to describe data.
Data can be nested
Fields can change over time.
Support for new types (arrays etc)

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7
Q

Databases Shared Responsibility Model

A

AWS offers use to manage different databases
Benefits include:
Quick provisioning
High availability
Vertical and horizontal scaling
Automated backup and restore, operations and upgrades
Operating System Patching is handled by AWS
Monitoring and Alerting

If run on EC2 instance, you need to handle resiliency, backup, patching, high availability, fault tolerance, scaling, etc.

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8
Q

RDS

A

Relational Database Service

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9
Q

RDS Overview

A

Relational Database
Managed DB
Uses SQL

Create databases in cloud that are managed by AWS
Postgres
MySQL
MariaDB
Oracle
Microsoft SQL Server
IDM DB2
Aurora

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9
Q

DB

A

database

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10
Q

RDS vs EC2

A

managed vs not
Automated provisioning and patching
continuous backups and restore
monitoring dashboards
read replicas
multi AZ setup for DR (disaster recovery)
Scaling capability
Storage backed by EBS

CANNOT SSH into your instances

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11
Q

RDS Solution Architecture

A

Elastic Load Balancer -> EC2 Instances <—> Amazon RDS

Run as managed Service

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12
Q

Amazon Aurora

A

Proprietary to AWS
supports PostgreSQL and MySQL

Cloud optimized

Storages grows automatically in increments of 10gb up to 128 TB

20% more efficient than RDS

Not in free tier

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13
Q

AWS Aurora Serverless

A

Automated database instantiation and auto-scaling based on actual use.

PostgreSQL and MySQL are both supported

No capacity planning needed

Least management overhead

Pay per second, can be more cost effective

Use cases: good for infrequent intermittent or unpredictable workload

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14
Q

RDS Deployment

A

Read Replicas
Multi-AZ
Multi-Region

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15
Q

Read Replicas

A

Up to 15 read replicas

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16
Q

Multi-AZ

A

Failover in case of AZ outage (high availability)

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17
Q

Multi-Region

A
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18
Q

Elastic Cache

A
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19
Q

Managed Redis

A
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20
Q

Memcached

A
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21
Q

Dynamo DB

A
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22
Q
A
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23
Q
A
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24
Dynamo DB Global Tables
25
26
27
Redshift
28
29
30
EMR Overview
31
32
33
Athena Overview
34
35
36
Quicksight overview
37
38
39
DocumentDB overview
40
41
42
Neptune Overview
43
44
45
Timestream Overview
46
47
48
QLDB Overview
49
50
51
51
Managed Blockchain
52
53
54
Glue Overview
55
56
57
DMS Overview
58
59
Relational Database - OLTP
RDS & Aurorara (SQL)
60
In-memory Database
ElasticCache
61
Key/Value Database
DynamoDB(serverless) & DAX (cache for DynamoDB)
62
Multi-AZ vs Read Replicas vs Multi-Region
63
Warehouse - OLAP
Redshift (SQL)
64
OLAP
online analytical processing
65
Hadoop Cluster
EMR
66
Athena
Query data on Amazon S3 (serverless & SQL)
67
Quicksight
dashboards on your database (serverless)
68
DocumentDB
Aurora for MongoDB (JSON- NoSQL database)
69
MongoDB
70
QLDB
71
Amazon QLDB
Financial Transaction Ledger Immutable journal, cryptographically verifiable
72
Amazon Managed Blockchain
Managed Hyperledger Fabric and Ethereum blockchains
73
Glue
Managed ETL (Extract Transform Load) and Data Catalog Service
74
ETL
75
Data Catalog Service
76
Managed Hyperledger Fabric
77
Database Migration
DMS Database Migration Service
78
Neptune
Graph Database
79
Graph Database
80
Timestream
Time-series database
81
Time-series database
82
OLTP
83
What does in memory database mean?
84
What does key/value database mean?
85
What is a Hadoop Cluster
86
What is Hadoop?