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1

AWSプロダクトシリーズ

よくわかるAmazon Redshift

2014/02/19
アマゾン データ サービス ジャパン株式会社

2

Amazon Redshift
Fast, simple, petabyte-scale data warehousing for less than $1,000/TB/Year
Rahul Pathak |Senior Product Manager

3

a lot faster
a lot cheaper
a whole lot simpler

Petabyte scale

Massively parallel
Amazon
Redshift

Relational data warehouse
Fully managed; zero admin

4

Amazon Redshift Quick Overview
Amazon Redshift 概要のおさらい

5

Amazon Redshift architecture
•

Leader Node
–
–
–

•

SQL endpoint
Stores metadata
Coordinates query execution

JDBC/ODBC

Compute Nodes
–
–
–
–

Local, columnar storage
Execute queries in parallel
Load, backup, restore via
Amazon S3
Parallel load from Amazon DynamoDB

•

Hardware optimized for data processing

•

Two hardware platforms

10 GigE
(HPC)

–
–

DW1: HDD; scale from 2TB to 1.6PB
DW2: SSD; scale from 160GB to 256TB

Ingestion
Backup
Restore

6

Amazon Redshift has security built-in
•
•

Customer VPC

SSL to secure data in transit
Encryption to secure data at rest
–
–
–

JDBC/ODBC

AES-256; hardware accelerated
All blocks on disks and in Amazon S3
encrypted
HSM Support

•

10 GigE
(HPC)

No direct access to compute nodes

•

Internal
VPC

Audit logging & AWS CloudTrail
integration

•

Amazon VPC support

Ingestion
Backup
Restore

7

Amazon Redshift is easy to use
•

Provision in minutes

•

Monitor query performance

•

Point and click resize

•

Built in security

•

Automatic backups

8

Provision a data warehouse in minutes

9

Monitor query performance

10

Point and click resize

•

Resize while remaining online via AWS
Console or API

•

Provision a new cluster in the background
and copy data in parallel from node to
node

•

Only charged for source cluster until SQL
endpoint has automatically been switched
over via DNS

11

Amazon Redshift continuously backs up your data and
recovers from failures
•

Replication within the cluster and backup to Amazon S3 to maintain multiple
copies of data at all times

•

Backups to Amazon S3 are continuous, automatic, and incremental
–

Designed for eleven nines of durability

•

Continuous monitoring and automated recovery from failures of drives and nodes

•

Able to restore snapshots to any Availability Zone within a region

•

Easily enable backups to a second region for disaster recovery

12

Amazon Redshift integrates with multiple data sources

Corporate Datacenter

DynamoDB

Amazon Redshift

Amazon S3

Amazon RDS

Amazon EMR

13

New Features That Introduced After re:Invent 2013
re:Invent 2013以降の主なアップデート

14

Feature Delivery in 2013
Unload logs (7/5)
Temp Credentials (4/11)

Sharing snapshots (7/18)

DUB (4/25)

Resource Level IAM (8/9)
SHA1 Builtin (7/15)

SOC1/2/3 (5/8)
Statement Timeout (7/22)
WLM Timeout/Wildcards (8/1)
UTF-8 Substitution (8/29)

JDBC Fetch Size (6/27)

Kinesis EMR/HDFS/SSH copy,
Distributed Tables, Audit
Logging/CloudTrail, Concurrency,
Resize Perf., Approximate Count
Distinct, SNS Alerts (11/13)

Service Launch (2/14)
Split_part, Audit tables (10/3)
EIP Support for VPC Clusters (12/28)

PCI (8/22)
SIN/SYD (10/8)
PDX (4/2)

Distributed Tables, Single Node Cursor
Support, Maximum Connections to 500
(12/13)

JSON, Regex, Cursors (9/10)

NRT (6/5)

CRC32 Builtin, CSV, Restore Progress
(8/9)
Timezone, Epoch, Autoformat (7/25)
4 byte UTF-8 (7/18)

Unload Encrypted Files

HSM Support (11/11)

15

Summary of Updates after re:Invent
•

Amazon Redshift - New Features Galore (2013/11/11)
–
–
–
–

–
–
–
–

•
•
•

Distributed Tables - You now have more control over the distribution of a table's rows across compute
nodes.
Remote Loading - You can now load data into Redshift from remote hosts across an SSH connection.
Approximate Count Distinct - You can now use a variant of the COUNT function to approximate the
number of matching rows.
Workload Queue Memory Management - You can now apportion available memory across work
queues.
Key Rotation - You can now direct Redshift to rotate keys for an encrypted cluster.
HSM Support - You can now direct Redshift to use an on-premises Hardware Security Module (HSM) or
AWS CloudHSM to manage the encryption master and cluster encryption keys.
Database Auditing and Logging - You can log connections and user activity to Amazon S3.
SNS Notification - Redshift can now issue notifications to an Amazon SNS topic when certain events
occur.

Automated Cross-Region Snapshot Copy for Amazon Redshift (2013/11/14)
Faster & More Cost-Effective SSD-Based Nodes for Amazon Redshift(2014/01/24)
AWS CloudFormation Adds Support for Redshift and More (2014/02/10)

16

Amazon Redshift Node Types
DW1.XL: 16 GB RAM, 2 Cores
3 Spindles, 2 TB compressed storage

•

Optimized for I/O intensive workloads

•

High disk density

DW1.8XL: 128 GB RAM, 16 Cores, 24
Spindles 16 TB compressed, 2 GB/sec scan
rate

•

On demand at $0.85/hour

•

As low as $1,000/TB/Year

•

Scale from 2TB to 1.6PB

DW2.L *New*: 16 GB RAM, 2 Cores,
160 GB compressed SSD storage

•

High performance at smaller storage size

•

High compute and memory density

•

On demand at $0.25/hour

•

As low as $5,500/TB/Year

•

Scale from 160GB to 256TB

DW2.8XL *New*: 256 GB RAM, 32 Cores,
2.56 TB of compressed SSD storage

17

Amazon Redshift is priced to let you analyze all your data
Price Per Hour for
DW1.XL Single Node

Effective Annual
Price per TB

On-Demand

$ 1.250

$ 5,475

1 Year Reservation

$ 0.750

$ 3,283

3 Year Reservation

$ 0.452

$ 1,981

DW1 (HDD)

Effective Annual
Price per TB

On-Demand

$ 0.330

$ 18,068

1 Year Reservation

$ 0.211

$ 11,570

3 Year Reservation

$ 0.130

$ 7,127

No charge for leader node

•
Price Per Hour for
DW2.L Single Node

Number of nodes x cost per
hour

•

DW2 (SSD)

•

No upfront costs

•

Pay as you go

18

Security, visibility and control
•

Audit logging
Redshift

•

SNS Alerts

19

Visibility and control

AWS
CloudTrail
System Activity
Creates, Changes,
Deletes, Resizes

•

Audit logging

•

SNS Alerts

Amazon Redshift

Database Activity
Logins, Login failures,
Queries, Loads

Amazon S3

20

Visibility and control
•
•

Audit logging
Monitoring
Security
Maintenance
Errors

SNS Alerts
Amazon
Redshift

SNS
Topic

21

Batch operations
•

Cluster Creation

•

Faster Resize

Amazon Corporate Amazon
EC2 Data Center EMR

Amazon
Redshift

Amazon S3

22

Batch operations
•

Cluster Creation

•

Faster Resize

Amazon Corporate Amazon
EC2 Data Center EMR

Amazon
Redshift

Amazon S3

23

Batch operations
•

Cluster Creation

•

Faster Resize

15-20 min

3 min

24

Batch operations
•

Cluster Creation

•

Faster Resize

29 hours

7 hours

25

Performance & Concurrency

26

Performance & Concurrency

692.8s

34.9s
< 2%

27

Performance & Concurrency

5,951.7s
2,151.9s

28

Performance & Concurrency

15

50

29

How Customers Leverage Amazon Redshift
Amazon Redshift 活用事例

30

Common Customer Use Cases

Traditional Enterprise DW

SaaS Companies

•

Improve performance by
an order of magnitude

•

Add analytic functionality
to applications

Make more data
available for analysis

•

Scale DW capacity as
demand grows

•

•

•

•

•

Reduce costs by
extending DW rather than
adding HW

Companies with Big Data

Access business data via
standard reporting tools

•

Reduce HW & SW costs
by an order of magnitude

Migrate completely from
existing DW systems
Respond faster to
business; provision in
minutes

31

Amazon Redshift Customers

32

Japanese Redshift Customer – ALBERT
•

Business Challenge
–

•

Why AWS?
–

–

•

Given their data volumes, RDBMS tuning and archiving was causing them a lot of
operational pain and costing them money

Amazon Redshift’s performance and ability to handle large data sets allowed them to
make it the core engine of their analytics, enabling them to provide a private DMP (Data
Management Platform) for their customers on the Cloud
PostgreSQL is their primary RDBMS, and connectivity by PostgreSQL drivers is big technical
advantage to choose Redshift.

Benefits for their business
–
–

Ability to start small and scale as needed
Scalability and flexibility dramatically lowered the cost of ownership

33

Japanese Redshift Customer – Sansan
•

Business Challenge
– Since “Eight” is business card management solution for consumers, they
needed infrastructure that could start small and scale as needed

•

Why AWS?
– When they tried out AWS first, they were surprised with the ease of use. AWS
functionality and elasticity were critical factors

•

Benefits for their business
– Lower costs substantially using reserved instances
– Automation is a key to reduce operational and administration costs. They
utilize services such as Amazon SES and Amazon SWF.
– They use Redshift for KPI analytics of their services.

34

Growing ecosystem

35

Multiple Data Loading Options
Data Integration

•

Parallel upload to Amazon S3

•

AWS Direct Connect

•

AWS Import/Export

•

ETL Software

•

Systems integrators

Systems Integrators

36

Customers on Performance
“Redshift is twenty times faster than Hive” (5x – 20x reduction in query times) link

…[Redshift] performance has blown away everyone here (we generally see 50-100x speedup
over Hive). link
“We saw…2x improvement in query times and a 50% reduction in costs”
We regularly process multibillion row datasets and we do that in a matter of hours. link
“Queries that used to take hours came back in seconds. Our analysts are orders of magnitude
more productive.” (20x – 40x reduction in query times) link
“Did I mention it's ridiculously fast? We'll be using it immediately to provide our analysts
an alternative to Hadoop.”

37

Customers on Cost
“We found that Amazon Redshift offers the performance we needed while freeing us from
the licensing costs of our previous solution” link
“[Redshift] cost saving is even more impressive…Our analysts like [Redshift] so much they
don’t want to go back.” (4x reduction in cost over HIVE) link
“We saw 50% reduction in costs”
“Not only did we avoid 3 months of development work [we] saved approximately $80,000 in
labor…Competitive Advantage realized with just a few clicks.”
“[Amazon Redshift] took an industry famous for its opaque pricing, high TCO and unreliable
results and completely turned it on its head.” link
“[Redshift] has reduced our storage and processing costs significantly, helping us to realize
another 60-70 percent savings.” link

38

Customer on Ease of Use
“With Amazon Redshift and Tableau, anyone in the company can set up any queries they
like…It’s very flexible.” link
“Compared to Hadoop [Redshift] is much easier for analysts to use. What may have been a
Hadoop project can become just a query in Redshift.” link

“We can spin up an Amazon Redshift cluster, take a snapshot, and scale servers in minutes
instead of days.” link
“…our team was able to provision Redshift in a matter hours vs. weeks with on-premises
servers.”
“Amazon Redshift is simple to use and reliable. With one click, we can rapidly scale up or down
in real time in alignment with business requirements.” link
“Customers can get consistent, accurate, and useful data fast - in weeks not months or years.”
link

39

AWS Marketplace
•

Find software to use with Amazon
Redshift

•

One-click deployments

•

Flexible pricing options

http://aws.amazon.com/marketplace

40

Questions?

41

APPENDIX

42

Resources
•

Detail Pages
–
–

•

New Features
–
–

•

http://docs.aws.amazon.com/redshift/latest/dg/doc-history.html
http://docs.aws.amazon.com/redshift/latest/mgmt/document-history.html

Best Practices
–
–
–

•

http://aws.amazon.com/redshift
https://aws.amazon.com/marketplace/redshift/

http://docs.aws.amazon.com/redshift/latest/dg/c_loading-data-best-practices.html
http://docs.aws.amazon.com/redshift/latest/dg/c_designing-tables-best-practices.html
http://docs.aws.amazon.com/redshift/latest/dg/c-optimizing-query-performance.html

Presentations & Webinars:
–
–
–

http://www.youtube.com/watch?v=JxLpj_TnisM (2013 SF Summit Presentation)
http://www.youtube.com/watch?v=R1m-fwzXMow (Best Practices 1 of 2)
http://www.youtube.com/watch?v=7ySzRTOyK6o (Best Practices 2 of 2)

43

Amazon Redshift dramatically reduces I/O
Column storage
Data compression

Age

State

Amount

20

CA

500

345

25

WA

250

678

•

ID
123

•

40

FL

125

37

WA

375

•

Zone maps

957

•

Direct-attached storage

•

With row storage you do
unnecessary I/O

•

To get total amount, you have to
read everything

44

Amazon Redshift dramatically reduces I/O
Column storage
Data compression

Age

State

Amount

20

CA

500

345

25

WA

250

678

•

ID
123

•

40

FL

125

37

WA

375

•

Zone maps

957

•

Direct-attached storage

•

With column storage, you only
read the data you need

45

Amazon Redshift dramatically reduces I/O
•

Column storage

analyze compression listing;
Table |
Column
| Encoding
---------+----------------+---------listing | listid
| delta
listing | sellerid
| delta32k
listing | eventid
| delta32k
listing | dateid
| bytedict
listing | numtickets
| bytedict
listing | priceperticket | delta32k
listing | totalprice
| mostly32
listing | listtime
| raw

•

Data compression

•

Zone maps

•

Direct-attached storage

•

COPY compresses automatically

•

You can analyze and override

•

More performance, less cost

Slides not intended for redistribution.

46

Amazon Redshift dramatically reduces I/O
•

Column storage

10
324

•

Data compression

375

623

•

Zone maps

•

Direct-attached storage

637
959

10 | 13 | 14 | 26 |…
… | 100 | 245 | 324

375 | 393 | 417…
… 512 | 549 | 623
637 | 712 | 809 …
… | 834 | 921 | 959

•

Track the minimum and maximum
value for each block

•

Skip over blocks that don’t contain
relevant data

47

Amazon Redshift dramatically reduces I/O
•

Column storage
•

Use local storage for performance

•

Maximize scan rates

•

Data compression

•

Zone maps

•

Automatic replication and
continuous backup

•

Direct-attached storage

•

HDD & SSD platforms

48

Amazon Redshift parallelizes and distributes everything
•

Query

•

Load

•

Backup/Restore

•

Resize

49

Amazon Redshift parallelizes and distributes everything
•

Query

•

Load

•

Backup/Restore

•

Resize

•

Load in parallel from Amazon S3 or
Amazon DynamoDB or any SSH
connection

•

Data automatically distributed and
sorted according to DDL

•

Scales linearly with number of nodes

50

Amazon Redshift parallelizes and distributes everything
•

Query

•

Load

•

Backup/Restore

•

Backups to Amazon S3 are automatic, continuous
and incremental

•

Resize

•

Configurable system snapshot retention period. Take
user snapshots on-demand

•

Cross region backups for disaster recovery

•

Streaming restores enable you to resume querying
faster

51

Amazon Redshift parallelizes and distributes everything
•

Query

•

Load

•

Backup/Restore

•

Resize

•

Resize while remaining online

•

Provision a new cluster in the background

•

Copy data in parallel from node to node

•

Only charged for source cluster

52

Amazon Redshift parallelizes and distributes everything
•

Query

•

Load

•

Backup/Restore
•

•

Automatic SQL endpoint switchover
via DNS

•

Decommission the source cluster

•

Simple operation via Console or API

Resize

More Related Content

[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介

  • 2. Amazon Redshift Fast, simple, petabyte-scale data warehousing for less than $1,000/TB/Year Rahul Pathak |Senior Product Manager
  • 3. a lot faster a lot cheaper a whole lot simpler Petabyte scale Massively parallel Amazon Redshift Relational data warehouse Fully managed; zero admin
  • 4. Amazon Redshift Quick Overview Amazon Redshift 概要のおさらい
  • 5. Amazon Redshift architecture • Leader Node – – – • SQL endpoint Stores metadata Coordinates query execution JDBC/ODBC Compute Nodes – – – – Local, columnar storage Execute queries in parallel Load, backup, restore via Amazon S3 Parallel load from Amazon DynamoDB • Hardware optimized for data processing • Two hardware platforms 10 GigE (HPC) – – DW1: HDD; scale from 2TB to 1.6PB DW2: SSD; scale from 160GB to 256TB Ingestion Backup Restore
  • 6. Amazon Redshift has security built-in • • Customer VPC SSL to secure data in transit Encryption to secure data at rest – – – JDBC/ODBC AES-256; hardware accelerated All blocks on disks and in Amazon S3 encrypted HSM Support • 10 GigE (HPC) No direct access to compute nodes • Internal VPC Audit logging & AWS CloudTrail integration • Amazon VPC support Ingestion Backup Restore
  • 7. Amazon Redshift is easy to use • Provision in minutes • Monitor query performance • Point and click resize • Built in security • Automatic backups
  • 8. Provision a data warehouse in minutes
  • 10. Point and click resize • Resize while remaining online via AWS Console or API • Provision a new cluster in the background and copy data in parallel from node to node • Only charged for source cluster until SQL endpoint has automatically been switched over via DNS
  • 11. Amazon Redshift continuously backs up your data and recovers from failures • Replication within the cluster and backup to Amazon S3 to maintain multiple copies of data at all times • Backups to Amazon S3 are continuous, automatic, and incremental – Designed for eleven nines of durability • Continuous monitoring and automated recovery from failures of drives and nodes • Able to restore snapshots to any Availability Zone within a region • Easily enable backups to a second region for disaster recovery
  • 12. Amazon Redshift integrates with multiple data sources Corporate Datacenter DynamoDB Amazon Redshift Amazon S3 Amazon RDS Amazon EMR
  • 13. New Features That Introduced After re:Invent 2013 re:Invent 2013以降の主なアップデート
  • 14. Feature Delivery in 2013 Unload logs (7/5) Temp Credentials (4/11) Sharing snapshots (7/18) DUB (4/25) Resource Level IAM (8/9) SHA1 Builtin (7/15) SOC1/2/3 (5/8) Statement Timeout (7/22) WLM Timeout/Wildcards (8/1) UTF-8 Substitution (8/29) JDBC Fetch Size (6/27) Kinesis EMR/HDFS/SSH copy, Distributed Tables, Audit Logging/CloudTrail, Concurrency, Resize Perf., Approximate Count Distinct, SNS Alerts (11/13) Service Launch (2/14) Split_part, Audit tables (10/3) EIP Support for VPC Clusters (12/28) PCI (8/22) SIN/SYD (10/8) PDX (4/2) Distributed Tables, Single Node Cursor Support, Maximum Connections to 500 (12/13) JSON, Regex, Cursors (9/10) NRT (6/5) CRC32 Builtin, CSV, Restore Progress (8/9) Timezone, Epoch, Autoformat (7/25) 4 byte UTF-8 (7/18) Unload Encrypted Files HSM Support (11/11)
  • 15. Summary of Updates after re:Invent • Amazon Redshift - New Features Galore (2013/11/11) – – – – – – – – • • • Distributed Tables - You now have more control over the distribution of a table's rows across compute nodes. Remote Loading - You can now load data into Redshift from remote hosts across an SSH connection. Approximate Count Distinct - You can now use a variant of the COUNT function to approximate the number of matching rows. Workload Queue Memory Management - You can now apportion available memory across work queues. Key Rotation - You can now direct Redshift to rotate keys for an encrypted cluster. HSM Support - You can now direct Redshift to use an on-premises Hardware Security Module (HSM) or AWS CloudHSM to manage the encryption master and cluster encryption keys. Database Auditing and Logging - You can log connections and user activity to Amazon S3. SNS Notification - Redshift can now issue notifications to an Amazon SNS topic when certain events occur. Automated Cross-Region Snapshot Copy for Amazon Redshift (2013/11/14) Faster & More Cost-Effective SSD-Based Nodes for Amazon Redshift(2014/01/24) AWS CloudFormation Adds Support for Redshift and More (2014/02/10)
  • 16. Amazon Redshift Node Types DW1.XL: 16 GB RAM, 2 Cores 3 Spindles, 2 TB compressed storage • Optimized for I/O intensive workloads • High disk density DW1.8XL: 128 GB RAM, 16 Cores, 24 Spindles 16 TB compressed, 2 GB/sec scan rate • On demand at $0.85/hour • As low as $1,000/TB/Year • Scale from 2TB to 1.6PB DW2.L *New*: 16 GB RAM, 2 Cores, 160 GB compressed SSD storage • High performance at smaller storage size • High compute and memory density • On demand at $0.25/hour • As low as $5,500/TB/Year • Scale from 160GB to 256TB DW2.8XL *New*: 256 GB RAM, 32 Cores, 2.56 TB of compressed SSD storage
  • 17. Amazon Redshift is priced to let you analyze all your data Price Per Hour for DW1.XL Single Node Effective Annual Price per TB On-Demand $ 1.250 $ 5,475 1 Year Reservation $ 0.750 $ 3,283 3 Year Reservation $ 0.452 $ 1,981 DW1 (HDD) Effective Annual Price per TB On-Demand $ 0.330 $ 18,068 1 Year Reservation $ 0.211 $ 11,570 3 Year Reservation $ 0.130 $ 7,127 No charge for leader node • Price Per Hour for DW2.L Single Node Number of nodes x cost per hour • DW2 (SSD) • No upfront costs • Pay as you go
  • 18. Security, visibility and control • Audit logging Redshift • SNS Alerts
  • 19. Visibility and control AWS CloudTrail System Activity Creates, Changes, Deletes, Resizes • Audit logging • SNS Alerts Amazon Redshift Database Activity Logins, Login failures, Queries, Loads Amazon S3
  • 20. Visibility and control • • Audit logging Monitoring Security Maintenance Errors SNS Alerts Amazon Redshift SNS Topic
  • 21. Batch operations • Cluster Creation • Faster Resize Amazon Corporate Amazon EC2 Data Center EMR Amazon Redshift Amazon S3
  • 22. Batch operations • Cluster Creation • Faster Resize Amazon Corporate Amazon EC2 Data Center EMR Amazon Redshift Amazon S3
  • 29. How Customers Leverage Amazon Redshift Amazon Redshift 活用事例
  • 30. Common Customer Use Cases Traditional Enterprise DW SaaS Companies • Improve performance by an order of magnitude • Add analytic functionality to applications Make more data available for analysis • Scale DW capacity as demand grows • • • • • Reduce costs by extending DW rather than adding HW Companies with Big Data Access business data via standard reporting tools • Reduce HW & SW costs by an order of magnitude Migrate completely from existing DW systems Respond faster to business; provision in minutes
  • 32. Japanese Redshift Customer – ALBERT • Business Challenge – • Why AWS? – – • Given their data volumes, RDBMS tuning and archiving was causing them a lot of operational pain and costing them money Amazon Redshift’s performance and ability to handle large data sets allowed them to make it the core engine of their analytics, enabling them to provide a private DMP (Data Management Platform) for their customers on the Cloud PostgreSQL is their primary RDBMS, and connectivity by PostgreSQL drivers is big technical advantage to choose Redshift. Benefits for their business – – Ability to start small and scale as needed Scalability and flexibility dramatically lowered the cost of ownership
  • 33. Japanese Redshift Customer – Sansan • Business Challenge – Since “Eight” is business card management solution for consumers, they needed infrastructure that could start small and scale as needed • Why AWS? – When they tried out AWS first, they were surprised with the ease of use. AWS functionality and elasticity were critical factors • Benefits for their business – Lower costs substantially using reserved instances – Automation is a key to reduce operational and administration costs. They utilize services such as Amazon SES and Amazon SWF. – They use Redshift for KPI analytics of their services.
  • 35. Multiple Data Loading Options Data Integration • Parallel upload to Amazon S3 • AWS Direct Connect • AWS Import/Export • ETL Software • Systems integrators Systems Integrators
  • 36. Customers on Performance “Redshift is twenty times faster than Hive” (5x – 20x reduction in query times) link …[Redshift] performance has blown away everyone here (we generally see 50-100x speedup over Hive). link “We saw…2x improvement in query times and a 50% reduction in costs” We regularly process multibillion row datasets and we do that in a matter of hours. link “Queries that used to take hours came back in seconds. Our analysts are orders of magnitude more productive.” (20x – 40x reduction in query times) link “Did I mention it's ridiculously fast? We'll be using it immediately to provide our analysts an alternative to Hadoop.”
  • 37. Customers on Cost “We found that Amazon Redshift offers the performance we needed while freeing us from the licensing costs of our previous solution” link “[Redshift] cost saving is even more impressive…Our analysts like [Redshift] so much they don’t want to go back.” (4x reduction in cost over HIVE) link “We saw 50% reduction in costs” “Not only did we avoid 3 months of development work [we] saved approximately $80,000 in labor…Competitive Advantage realized with just a few clicks.” “[Amazon Redshift] took an industry famous for its opaque pricing, high TCO and unreliable results and completely turned it on its head.” link “[Redshift] has reduced our storage and processing costs significantly, helping us to realize another 60-70 percent savings.” link
  • 38. Customer on Ease of Use “With Amazon Redshift and Tableau, anyone in the company can set up any queries they like…It’s very flexible.” link “Compared to Hadoop [Redshift] is much easier for analysts to use. What may have been a Hadoop project can become just a query in Redshift.” link “We can spin up an Amazon Redshift cluster, take a snapshot, and scale servers in minutes instead of days.” link “…our team was able to provision Redshift in a matter hours vs. weeks with on-premises servers.” “Amazon Redshift is simple to use and reliable. With one click, we can rapidly scale up or down in real time in alignment with business requirements.” link “Customers can get consistent, accurate, and useful data fast - in weeks not months or years.” link
  • 39. AWS Marketplace • Find software to use with Amazon Redshift • One-click deployments • Flexible pricing options http://aws.amazon.com/marketplace
  • 42. Resources • Detail Pages – – • New Features – – • http://docs.aws.amazon.com/redshift/latest/dg/doc-history.html http://docs.aws.amazon.com/redshift/latest/mgmt/document-history.html Best Practices – – – • http://aws.amazon.com/redshift https://aws.amazon.com/marketplace/redshift/ http://docs.aws.amazon.com/redshift/latest/dg/c_loading-data-best-practices.html http://docs.aws.amazon.com/redshift/latest/dg/c_designing-tables-best-practices.html http://docs.aws.amazon.com/redshift/latest/dg/c-optimizing-query-performance.html Presentations & Webinars: – – – http://www.youtube.com/watch?v=JxLpj_TnisM (2013 SF Summit Presentation) http://www.youtube.com/watch?v=R1m-fwzXMow (Best Practices 1 of 2) http://www.youtube.com/watch?v=7ySzRTOyK6o (Best Practices 2 of 2)
  • 43. Amazon Redshift dramatically reduces I/O Column storage Data compression Age State Amount 20 CA 500 345 25 WA 250 678 • ID 123 • 40 FL 125 37 WA 375 • Zone maps 957 • Direct-attached storage • With row storage you do unnecessary I/O • To get total amount, you have to read everything
  • 44. Amazon Redshift dramatically reduces I/O Column storage Data compression Age State Amount 20 CA 500 345 25 WA 250 678 • ID 123 • 40 FL 125 37 WA 375 • Zone maps 957 • Direct-attached storage • With column storage, you only read the data you need
  • 45. Amazon Redshift dramatically reduces I/O • Column storage analyze compression listing; Table | Column | Encoding ---------+----------------+---------listing | listid | delta listing | sellerid | delta32k listing | eventid | delta32k listing | dateid | bytedict listing | numtickets | bytedict listing | priceperticket | delta32k listing | totalprice | mostly32 listing | listtime | raw • Data compression • Zone maps • Direct-attached storage • COPY compresses automatically • You can analyze and override • More performance, less cost Slides not intended for redistribution.
  • 46. Amazon Redshift dramatically reduces I/O • Column storage 10 324 • Data compression 375 623 • Zone maps • Direct-attached storage 637 959 10 | 13 | 14 | 26 |… … | 100 | 245 | 324 375 | 393 | 417… … 512 | 549 | 623 637 | 712 | 809 … … | 834 | 921 | 959 • Track the minimum and maximum value for each block • Skip over blocks that don’t contain relevant data
  • 47. Amazon Redshift dramatically reduces I/O • Column storage • Use local storage for performance • Maximize scan rates • Data compression • Zone maps • Automatic replication and continuous backup • Direct-attached storage • HDD & SSD platforms
  • 48. Amazon Redshift parallelizes and distributes everything • Query • Load • Backup/Restore • Resize
  • 49. Amazon Redshift parallelizes and distributes everything • Query • Load • Backup/Restore • Resize • Load in parallel from Amazon S3 or Amazon DynamoDB or any SSH connection • Data automatically distributed and sorted according to DDL • Scales linearly with number of nodes
  • 50. Amazon Redshift parallelizes and distributes everything • Query • Load • Backup/Restore • Backups to Amazon S3 are automatic, continuous and incremental • Resize • Configurable system snapshot retention period. Take user snapshots on-demand • Cross region backups for disaster recovery • Streaming restores enable you to resume querying faster
  • 51. Amazon Redshift parallelizes and distributes everything • Query • Load • Backup/Restore • Resize • Resize while remaining online • Provision a new cluster in the background • Copy data in parallel from node to node • Only charged for source cluster
  • 52. Amazon Redshift parallelizes and distributes everything • Query • Load • Backup/Restore • • Automatic SQL endpoint switchover via DNS • Decommission the source cluster • Simple operation via Console or API Resize