In this presentation, Kaz Ohta, Kiyoto Tamura, and Ankush Rustagi from Treasure Data describe the company's Cloud Data Warehouse service.
"The Treasure Data Cloud Data Warehouse service enables companies to get big data analytics running in days not months without specialist IT resources and for a tenth the cost of other alternatives. Traditional data warehousing solutions - even modern alternatives such as Hadoop - are too expensive, complex and take too long for many companies to implement, so the idea of quickly launching a data warehouse service that uses the power and economics of the Cloud for companies of any size, opens up a huge potential market."
Learn more at: http://treasure-data.com * Watch the presentation video: http://inside-bigdata.com/?p=3531
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Treasure Data Cloud Data Platform
1. Hiro Yoshikawa, Founder and CEO
hiro@treasure-data.com
650-810-6184
Kazuki Ohta, Founder and CTO
k@treasure-data.com
650-223-5679
Treasure Data
Cloud Data Platform
Friday, August 2, 13
2. 2
Hiro Yoshikawa – CEO
- Open Source business veteran at Red Hat
Kazuki Ohta – CTO
- Founder of the World’s largest Hadoop group
Keith Goldstein – VP Business Dev
- VP of BD at TIBCO, Talend
Jeff Yuan - Engineering Director
- LinkedIn, MIT/Michael Stonebraker Lab
Investors (part):
Bill Tai - Chairman of the board
Jerry Yang – Yahoo! founder
James Lindenbaum – Heroku Founder
Yukihiro “Matz” Matsumoto – Ruby creator
Othman Laraki - ex-VP Growth at Twitter
Business, Team & Investors
Founded to deliver big data
analytics in days not months without
specialist IT resources
Service based subscription
business model
Treasure Data is in production for
80+ customers
• incl. Fortune 500 companies
• 500+ billion records stored
• Wide variety of use casen
World class team
• Great open source team
• Top investors
Friday, August 2, 13
3. The Problem with Other Solutions
3
Customer
Value
Time
Sign-up or PO
On-Premise
Solutions
Obsolescence
over time
Treasure Data
Fully integrated Big Data full-
stack service with simple
interface, low friction initial
engagement & continuous
technical upgrade
Need Upgrade
AWS
(or hosted Hadoops)EC2
EMR
RedShift
S3 Step-by-step manual
integrations
Maintain
NO SpecialistsTOO LONG to get Live
=
Complex Solutions
+
Data Collection
+
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4. Columnar Storage
+
Hadoop
MapReduce
500bil+ records
2mil+ jobs
Product
4
Data Collection Data Warehouse Data Analysis
Open-Source
Log Collector
2,000+ companies
(incl. LinkedIn, etc)
Bulk Loader
CSV / TSV
MySQL,
Postgres
Oracle, etc.
Web Log
App Log
Sensor
RDBMS
CRM
ERP
BI Tools
Tableau, QlikView
Excel, etc.
REST
JDBC / ODBC
SQL
(HiveQL)
Pig
Bulk Upload
Parallel Upload
Value Proposition:
“Time-to-Answer” 20bil+, 2 weeks,
UK/Austria
3bil+, 3 weeks
Singapore
2 weeks,
US
2 weeks,
US
3 weeks,
Japan
Dashboard
Custom App,
RDBMS, FTP, etc.
Result push
Multi-Tenant: Speed of Improvements + Ease of Management (e.g. SFDC, Heroku)
Streaming Upload
>80billion / month
JSON
(MsgPack)
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5. 5
A case: “14 Days” from Signup to Success
1. Europe’s largest mobile ad
exchange.
2. Serving >20 billion imps/
month for >15,000 mobile
apps (Q1 2013)
3. Immediate need of analytics
infrastructure: ASAP!
4. With TD, MobFox got into
production only in 14 days,
by one engineer.
"Time is the most precious asset in our fast-moving business,
and Treasure Data saved us a lot of it."
Julian Zehetmayr, CEO & Founder
td-agent =
fluentd rpm/deb
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6. 6
A case: “Replace” in-house Hadoop to TD
1. Global “Hulu” - Online Video
Service with millions of users
2. Video contents are distributed
to over 150 languages.
3. Had hard time maintaining
Hadoop cluster
4. With TD, Viki deprecated their
in-house Hadoop cluster and
use engineer for core
businesses.
Before
After
“Treasure Data has always given us thorough and timely support
peppered with insightful tips to make the best use of their service."
Huy Nguyen, Software Engineer
Friday, August 2, 13
7. 7
A case: Treasure Data with BI Tool (Tableau)
1. World’s largest android
application market
2. Serving >3 billion app
downloads for >100 million
users
3. Only one engineer managing
the data infrastructure
4. With TD, the data engineer can
focus on analyzing data with
existing BI tool
"I will recommend Treasure Data to my friends in a heartbeat because it
benefits all three stakeholders: Operations, Engineering and Business."
Simon Dong, Principal Architect - Data Engineering
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8. 8
AWS (IaaS)
Columnar Storage
Hadoop Hive / Pig
Low-Latency
Query Executor
Log Collector
REST API
&
Mgmt
Console
Data Mart
BI + Analytics tool connectivity
Dynamic Table Partitioning
Full-Stack Cloud Data Platform
Multi-Tenant
Inter-DC
FairScheduler
Resource
Isolation
Access
Control
Catalog
Services
Config
Automation
Other Cloud stack, on-premise
ANSI SQL
Bulk Loader Mobile SDK External Sources
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9. Competitive Landscape
Data Storage
On-Premise
Data collection
Hadoop Distro
Visualization, BI,
Analytical apps
Processing Platform
Connections/
Integrations
EMR
Flume
• Most big data players, regardless of
cloud or on-premise, have had
technical challenges in data
collection and trustful multi-
tenancy data storage design.
• Treasure Data solves both with
Fluentd and our own columnar DB
on top of cloud storage solutions
TD is the one
stop, full-
stack solution
Cloud
Redshift
Partnering
9
Friday, August 2, 13