This document discusses running databases on AWS. It provides an overview of several AWS database services including Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon ElastiCache. It highlights how these services provide scalability, reliability, automation of tasks like backups and patching, and pay-as-you-go pricing. It also discusses how AWS database services eliminate the need to manage hardware, databases, backups, and other complex tasks when compared to operating databases in an on-premises data center.

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

2. LoggingAnalytics
Webscale
Throughput
Rich Search
Hot Reads
Complex Queries
and Transactions
The Database

3. LoggingAnalytics
Webscale
Throughput
Rich Search
Hot Reads
Complex Queries
and Transactions
Amazon
DynamoDB
Amazon
RDS
Amazon
Elasticache
Amazon
S3
Amazon
Redshift
Amazon
Elasticsearch
The Data Tier

4. Analytics Webscale
Throughput
Complex Queries
and Transactions
Amazon
DynamoDB
Amazon
RDS
Amazon
Redshift
The Data Tier

5. Fully managed
Reliable
Scalable
Amazon
RDS
Amazon Aurora

6. 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?

7. 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

8. 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

9. Automated Backups
DB Snapshots
1
2
Backup & Restore

10. Default Metrics and Enhanced Monitoring
Alarms &
notifications
1
2
Monitoring and Alerting

11. AZ1 AZ2
Multi-AZ

12. Physical
Synchronous
Replication
AZ1 AZ2
Multi-AZ

13. Physical
Synchronous
Replication
AZ1 AZ2
Multi-AZ

14. AZ1 AZ2
Multi-AZ

15. AZ1 AZ2
Multi-AZ

16. AZ1 AZ2
DNS
Primary
Update
Multi-AZ

17. AZ1 AZ2
DNS
cname update
Primary
Update
Multi-AZ

18. AZ1 AZ2
DNS
cname update
Primary
Update
Multi-AZ

19. AZ1 AZ2
DNS
cname update
Primary
Update
Multi-AZ

20. • Compute • Network • Storage
Instance Class
• Memory
Storage Type
Performance

21. Magnetic
(HDD)
Provisioned
IOPS
(SSD)
General
Purpose
(SSD)
RDS Storage Types

22. Sync
Replication
Multi-AZ
Read Replicas

23. Async Replication
Read Replicas

24. Read Replicas
Async Replication

25. “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

26. Analytics Webscale
Throughput
Complex Queries
and Transactions
Amazon
DynamoDB
Amazon
RDS
Amazon
Redshift
The Data Tier

27. • MPP SQL Database
• Optimised for analytics
• Gigabytes to petabytes
• Fully relational
• Fully managed
Amazon
Redshift

28. 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

29. • 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

30. 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

31. • Column storage
• Data compression
• Zone maps
2-4 x
Reduces I/O

32. • 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

33. 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

34. 160 GB
DC1.L
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
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
8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL
8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL 8XL
2 PB
Scalability

35. JDBC/ODBC
Amazon Redshift
Works With Your Analytics tools

36. “We intend to grow 100x in terms of
data size in the next few years”
- Kaushik Paranjape, CTO

37. Analytics Webscale
Throughput
Complex Queries
and Transactions
Amazon
DynamoDB
Amazon
RDS
Amazon
Redshift
The Data Tier

38. Scalability
Data complexity
RDBMS
key/value
document
graph

39. • NoSQL database
• Key/Value + document
• Very low latency
• Fully managed
Amazon
DynamoDB

40. Low Latency

41. WRITES
Continuously replicated to 3 AZ’s
Persisted to disk (custom SSD)
READS
Strongly or
eventually consistent
Durability

42. “I was extremely comfortable running
our business-critical systems in an
AWS architecture.”
- Harry Teng CIO

43. Analytics Webscale
Throughput
Complex Queries
and Transactions
Amazon
DynamoDB
Amazon
RDS
Amazon
Redshift
The Data Tier

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