aws innovate: running databases in aws- russell nash

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Running Databases on AWS Russell Nash , Solutions Architect, Amazon Web Services

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Running Databases on AWSRussell Nash , Solutions Architect, Amazon Web Services

LoggingAnalyticsWebscale

Throughput

Rich SearchHot Reads

Complex Queries

and Transactions

The Database

LoggingAnalyticsWebscale

Throughput

Rich SearchHot Reads

Complex Queries

and Transactions

AmazonDynamoDB

AmazonRDS

AmazonElasticache

AmazonS3

AmazonRedshift

AmazonElasticsearch

The Data Tier

Analytics Webscale

Throughput

Complex Queries

and Transactions

AmazonDynamoDB

AmazonRDS

AmazonRedshift

The Data Tier

Fully managed

Reliable

ScalableAmazon

RDS

Amazon Aurora

Power, HVAC, net

Rack & stack

Server maintenance

OS patches

DB s/w patches

Database backups

Scaling

High availability

DB s/w installs

OS installation

Query Construction

Query Optimisation

Schema Design

Traditional

DC

Why Managed Databases?

Power, HVAC, net

Rack & stack

Server maintenance

OS patches

DB s/w patches

Database backups

Scaling

High availability

DB s/w installs

OS installation

Query Construction

Query Optimisation

Schema Design

Power, HVAC, net

Rack & stack

Server maintenance

OS patches

DB s/w patches

Database backups

Scaling

High availability

DB s/w installs

OS installation

Query Construction

Query Optimisation

Schema Design

DB

on EC2

Why Managed Databases?

Traditional

DC

Power, HVAC, net

Rack & stack

Server maintenance

OS patches

DB s/w patches

Database backups

Scaling

High availability

DB s/w installs

OS installation

Query Construction

Query Optimisation

Schema Design

Power, HVAC, net

Rack & stack

Server maintenance

OS patches

DB s/w patches

Database backups

Scaling

High availability

DB s/w installs

OS installation

Query Construction

Query Optimisation

Schema Design

Power, HVAC, net

Rack & stack

Server maintenance

OS patches

DB s/w patches

Database backups

Scaling

High availability

DB s/w installs

OS installation

Query Construction

Query Optimisation

Schema Design

Amazon

RDS

Why Managed Databases?

DB

on EC2

Traditional

DC

Automated Backups

DB Snapshots

1

2

Backup & Restore

Default Metrics and Enhanced Monitoring

Alarms &

notifications

1

2

Monitoring and Alerting

AZ1 AZ2

Multi-AZ

Physical

Synchronous

Replication

AZ1 AZ2

Multi-AZ

Physical

Synchronous

Replication

AZ1 AZ2

Multi-AZ

AZ1 AZ2

Multi-AZ

AZ1 AZ2

Multi-AZ

AZ1 AZ2

DNS

Primary

Update

Multi-AZ

AZ1 AZ2

DNS

cname update

Primary

Update

Multi-AZ

AZ1 AZ2

DNS

cname update

Primary

Update

Multi-AZ

AZ1 AZ2

DNS

cname update

Primary

Update

Multi-AZ

• Compute • Network • Storage

Instance Class

• Memory

Storage Type

Performance

Magnetic (HDD)

Provisioned IOPS (SSD)

General Purpose(SSD)

RDS Storage Types

Sync

Replication

Multi-AZ

Read Replicas

Async Replication

Read Replicas

Read Replicas

Async Replication

“In a physical data center, I would need at least 3

administrators to maintain the infrastructure and ensure

similar levels of availability”

- Richard Glew, CTO

Analytics Webscale

Throughput

Complex Queries

and Transactions

AmazonDynamoDB

AmazonRDS

AmazonRedshift

The Data Tier

• MPP SQL Database

• Optimised for analytics

• Gigabytes to petabytes

• Fully relational

• Fully managed

Amazon

Redshift

ID Name

1 John Smith

2 Jane Jones

3 Peter Black

4 Pat Partridge

5 Sarah Cyan

6 Brian Snail

1 John Smith

4 Pat Partridge

2 Jane Jones

5 Sarah Cyan

3 Peter Black

6 Brian Snail

Massively Parallel

JDBC/ODBC

• Column storage

• Data compression

• Zone maps

ID Age State Amou

nt

123 20 QLD 500

345 25 WA 250

678 40 NSW 125

957 37 WA 375

Reduces I/O

Row storage

Have to read the

entire row

Column storage

Only read the

data you need

• Column storage

• Data compression

• Zone maps

Reduces I/O

ID Age State Amou

nt

123 20 QLD 500

345 25 WA 250

678 40 NSW 125

957 37 WA 375

• Column storage

• Data compression

• Zone maps

2-4 x

Reduces I/O

• Column storage

• Data compression

• Zone maps

Reduces I/O

02-JAN-2016

04-JAN-2016

07-JAN-2016

08-JAN-2016

09-JAN-2016

10-JAN-2016

15-JAN-2016

21-JAN-2016

22-JAN-2016

29-JAN-2016

MIN: 02-JAN-2016

MAX: 09-JAN-2016

MIN: 10-JAN-2016

MAX: 29-JAN-2016

SELECT AVG(AMOUNT) WHERE SALES_DATE = 22-JAN-2016

Traditional

SQL Database

Amazon

Redshift

Summarise by month 02:08:35 00:35:46 00:00:12

Traditional

SQL Database

Amazon

Redshift

Performance – 2 Billion Rows

160 GB

DC1.L

8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL

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8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL

8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL

8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL

8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL

2 PB

Scalability

JDBC/ODBC

Amazon Redshift

Works With Your Analytics tools

“We intend to grow 100x in terms of

data size in the next few years”

- Kaushik Paranjape, CTO

Analytics Webscale

Throughput

Complex Queries

and Transactions

AmazonDynamoDB

AmazonRDS

AmazonRedshift

The Data Tier

Scalability

Data complexity

RDBMS

key/value

document

graph

• NoSQL database

• Key/Value + document

• Very low latency

• Fully managed

Amazon

DynamoDB

Low Latency

WRITES

Continuously replicated to 3 AZ’s

Persisted to disk (custom SSD)

READS

Strongly or

eventually consistent

Durability

“I was extremely comfortable running

our business-critical systems in an

AWS architecture.”

- Harry Teng CIO

Analytics Webscale

Throughput

Complex Queries

and Transactions

AmazonDynamoDB

AmazonRDS

AmazonRedshift

The Data Tier

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