With AWS you can choose the right database for the right job. Given the myriad of choices, from relational databases to non-relational stores, this session will profile details and examples of some of the choices available to you (MySQL, RDS, Elasticache, Redis, Cassandra, MongoDB and DynamoDB), with details on real world deployments from customers using Amazon RDS, ElastiCache and DynamoDB.

1. Jan Borch - AWS Solutions Architect
Understanding Database Options on AWS
Jan Borch
#awssummit
Berlin

2. We want to make it easy for you to start
1. Zero to Application in ____ Minutes
2. Zero to Millions of users in ____ Days
3. Zero to “Profits!” ASAP

3. Spot the critical component!

4. https://en.wikipedia.org/wiki/Comparison_of_relational_database_management_systems
http://nosql-database.org/

5. Spectrum of options on AWS
SQL NoSQL
Low Cost High Cost

Do-it-yourself Fully Managed
Not
available on
AWS

6. Spectrum of options on AWS
SQL NoSQL
Do-it-yourself Fully Managed

7. RDS
- MySQL
- Oracle
- SQL Server
MySQL
Oracle
SQL Server
PostgreSQL
Your favorite RDBMS
Spectrum of options on AWS
SQL NoSQL
Do-it-yourself Fully Managed

8. Spectrum of options on AWS
SQL NoSQL
Do-it-yourself Fully Managed
MongoDB
Cassandra
Redis
Memcached
…
Amazon DynamoDB
Amazon ElastiCache

9. Thinking about the questions
Should I use SQL or
NoSQL?
Should I use MySQL
on EC2 or RDS?
Should I use
MongoDB, Cassandra
, or DynamoDB?
Should I use
Redis, Memcached, or
ElastiCache?
?

10. Actually, thinking about the right questions
What are my scale
and latency needs?
What are my
transactional and
consistency needs?
What are my
read/write, storage
and IOPS needs?
What are my time to
market and server
control needs?
?

11. Focus on your application

12. Option 1:
Run your databases on EC2

13. Amazon Elastic Compute Cloud
Amazon EC2

14. Virtual core: 1
Memory: 1.7 GiB
I/O performance: Moderate
m1.small cc2.8xlarge
Virtual core: 32 - 2 x Intel Xeon
Memory: 60,5 GiB
I/O performance: 10 Gbit
cr1.8xlarge
Virtual core: 32 - 2 x Intel Xeon
Memory: 240 GiB
I/O performance: 10 Gbit
SSD Instance store: 240 GB
cr1.8xlarge
Virtual core: 16
Memory: 60.5 GiB
I/O performance: 10 Gbit
SSD Instance store: 2 x 1TB
cr1.8xlarge
Virtual core: 16
Memory: 117 GiB
I/O performance: 10 Gbit
Instance store: 24 x 2TB

16. Choose an Amazon Machine Image

17. Leverage AWS services
EBS storage Volumes with EBS Snapshots
S3 for backups (for example Oracle RMAN)
Automation with AWS API or CloudFormation

18. Option 2:
Let AWS manage my databases

19. backup & recovery,
data load & unload
performance
tuning
25%40%
5% 5%
scripting & coding
security
planning
install,
upgrade, patch
and migrate
documentation,
licensing &
training
differentiated effort
increases the
uniqueness
of an application
Why Managed Databases?

20. We believe in choice
One size does not fit all
Traditional Apps
Relational DB Needs
High
Performance, High
Scale Data
Warehouses
New Web Apps
Massive Scalability
Amazon RDS
Amazon
ElasticCache
Amazon
DynamoeDB
Amazon
Redshift

21. Option 2.1:
Managed SQL database

22. Amazon Relational Database Services
AmazonRDS
RDS is a fully managed relational database service
that is simple to deploy, easy to scale, reliable and
cost-effective

23. Choice of database options

24. Rapid deployment via Web Console

25. Backups and Recovery

26. Push Button Scaling
Scale …
• vertically up or down
• Storage vertically

27. Price
reduction
High Availability: Multi-AZ Deployments
Multi AZ price reductions
ranging from 15% to 32%

28. A few clicks or one API call

29. Horizontal Scaling with Read Replicas
New
Features
• Endpoint Renaming
• ReadReplica
to master promotion

30. A few clicks or one API call

31. High Performance RDS

32. Security
Oracle Native Network Encryption and Transparent
Data Encryption on Oracle EE
SSL support for SQL Server and mysql

33. Amazon RDS
Configuration
Improve
Availability
Increase
Throughput
Reduce
Latency
Push-Button Scaling
Multi-AZ
Read Replicas
Provisioned IOPS
Read ReplicasPush-Button Scaling
Provisioned IOPS
Region
Multi-AZ
Availability
Zone
Availability
Zone
Availability and performance options

34. Use case

35. Who is succeeding with RDS?
Thousands of developers use RDS every single day
Gaming Web Apps Mobile/Social Media

36. Amazon Elastic Cache
Amazon ElastiCache is a fully managed
Memcached-compatible caching service

37. Option 2.2:
Managed noSQL database

38. Amazon DynamoDB
Amazon DynamoDB is a fully managed NoSQL
database service

39. Single digit millisecond latency.
Backed on solid-state drives.
Consistent, predictable performance

40. No table size limits. Unlimited storage
No downtime.
Seamless scalability

41. Consistent, disk only writes.
Replication across data centers and availability
zones.
Durable

42. Without the operational burden.
managed by DynamoDB

43. Three click or on API call

44. Reserve IOPS for reads and writes.
Scale up for down at any time.
Provisioned throughput.

45. Pay per capacity unit
READ
Capacity Units =
Size of item (KB) x read per second
Consistent read:
$0.0065 for 50 read units
Eventually consistent reads:
$0.0065 for 100 read units
WRITE
Capacity Units =
Size of item (KB) x write per second
$0.0065 for 10 write units

46. Reserved capacity
Up to 53% for 1 year reservation
Up to 76% for 3 year reservation

47. Transactions
Item level transactions only
Puts, updates and deletes are ACID
Atomic increment and decrement
Conditional writes

48. Read Consistency
Strong or eventually consistent reads
Same latency expectations for strong
Mix and match at „read time‟

49. Data Modeling
Tables do not require a formal schema
Items are an arbitrarily sized hash.

50. id = 100
date = 2012-05-16-09-
00-10 total = 25.00
id = 101
date = 2012-05-15-15-
00-11 total = 35.00
id = 101
date = 2012-05-16-12-
00-10 total = 100.00
id = 102
date = 2012-03-20-18-
23-10 total = 20.00
id = 102
date = 2012-03-20-18-
23-10 total = 120.00
Data modeling
Table

51. id = 100
date = 2012-05-16-09-
00-10 total = 25.00
id = 101
date = 2012-05-15-15-
00-11 total = 35.00
id = 101
date = 2012-05-16-12-
00-10 total = 100.00
id = 102
date = 2012-03-20-18-
23-10 total = 20.00
id = 102
date = 2012-03-20-18-
23-10 total = 120.00
Data modeling
Item

52. id = 100
date = 2012-05-16-09-
00-10 total = 25.00
id = 101
date = 2012-05-15-15-
00-11 total = 35.00
id = 101
date = 2012-05-16-12-
00-10 total = 100.00
id = 102
date = 2012-03-20-18-
23-10 total = 20.00
id = 102
date = 2012-03-20-18-
23-10 total = 120.00
Data modeling
Attributes

53. Items are indexed by primary and secondary keys
Primary keys can be composite
Secondary keys are local to the table
Indexing

54. ID Date Total
Indexing

55. ID Date Total
Hash key
Indexing

56. ID Date Total
Hash key Range key
Composite primary key
Indexing

57. ID Date Total
Hash key Range key Secondary range key
Indexing

58. Programming DynamoDB.
Small but perfectly formed API.
CreateTable
UpdateTable
DeleteTable
DescribeTable
ListTables
PutItem
GetItem
UpdateItem
DeleteItem
BatchGetItem
BatchWriteItem
Query
Scan
Manage tables
Query specific
items OR scan the
full table
“Select”, “insert”,
“update” items
Bulk select or
update (max 1MB)

59. Query patterns
Retrieve all items by hash key.
Range key conditions:
==, <, >, >=, <=, begins with, between.
Counts. Top and bottom n values.
Paged responses.

60. 500,000 WRITES PER SECOND
DURING SUPER BOWL

61. Amazon DynamoDB: who is succeeding
with it?

62. Option 2.3:
Managed datawarehouse database

63. OLTP <-> OLAP
SELECT ProductID, Name
FROM Products
Where ProductID = 1234;
SELECT ProductID, count(*)
FROM Page_Hits
WHERE hour in (12,13)
GROUP BY ProductID

64. Transactional Processing
• Global context
– Daily revenue report
• Throughput
• Full table scans
• Sequential IO
• Disk Transfer rates
Analytical Processing
• Transactional context
– Get order total
• Latency
• Indexed access
• Random IO
• Disk Seek times
OLTP <-> OLAP

65. Amazon Redshift is a fast, fully managed, petabyte-scale
data warehouse service
Amazon Redshift

66. Fast and powerful
Parallelize and Distribute Everything
Dramatically Reduce I/O
Direct-attached storage
Large data block sizes
Column data store
Data compression
Zone maps
MPP
Load
Query
Resize
Backup
Restore

67. Fully Managed
Protect Operations
Simplify Provisioning
Redshift data is always encrypted
Continuously backed up to S3
Automatic node recovery
Transparent disk failure
Create a cluster in minutes
Automatic OS and software patching
Scale up to 1.6PB with a few clicks and no downtime

68. Amazon Redshift architecture
10 GigE
(HPC)
Ingestion
Backup
Restore
JDBC/ODBC

69. Focus on your application

70. Best of both worlds: Use both SQL and
NoSQL models in one app

71. More on Amazon Redshift?
03:15pm to 03:45pm
Introducing the Amazon Redshift data warehouse
Room Zero
Speaker: Steffen Krause, Amazon