Qubole provides data infrastructure as a service, allowing companies to query big data on the cloud. It manages over an exabyte of data for companies and has made data use more agile. The service is used by developers, analysts, and business users at some companies. It processes large amounts of data and clusters resources on demand to provide flexibility and reduce costs compared to building infrastructure in-house.

1. Qubole
Click to Query your Big Data on the Cloud

2. A company like Facebook provides Data
infrastructure as a service (created by the founders
of Qubole)
- More than 30% of the company uses this infrastructure
every month
- Users range from developers, analysts, business analysts or
business users
- Manages over an Exabyte of data
- Has made the company more data driven and agile with
data use
-It took the founders a team of over 30 people to create
this infrastructure and currently the team managing this
infrastructure has more than 100 people
2
Operations
Analyst
Marketing Ops
Analyst
Data
Architect
Business
Users
Product
Support
Customer
Support
Developer
Sales Ops
Product
Managers
Data
Infrastructure
QUBOLE VISION DATA FOR ALL CLICK-T0-QUERY

3. 3
~ 170+ PB of data processed
per month
10 – 3000 node clusters
on a daily basis
300,000 machines per month
20,000 jobs on a daily
basis
AGILITY TIME-TO-INSIGHT CLICK-T0-QUERY

4. CONFIDENTIAL. SUBJECT TO NDA PROVISIONS.
Industries and Use Cases
Media &
Advertising
Oil & Gas Retail Life Sciences Financial
Services
Security
Social
Networking &
Gaming
Targeted
Advertising
Seismic
Analysis
Image and
Video
Processing
Customer
Profile
Transaction
Analysis
Genome
Analysis
Monte Carlo
Simulations
Risk
Analysis
Fraud
Detection
Anti-virus
Image
Recognition
In-game
Metrics
Usage
Analysis
User
Demographics
Predefined
Reporting
Ad Hoc
Analytics
Statistical
Analytics
Predictive
Analytics
Machine
Learning
MapReduce Streaming
Workload Classifications
Match Your Processing Engines to Your Workload Parameters
SQL Data Pipeline MapReduce Spark NoSQL Store

5. AGILITY TIME-TO-INSIGHT CLICK-T0-QUERY
5
5
• 10-1000+ Nodes in <5min
• Flexible - different nodes for different loads
• Data For All - usable by many
• Low TCO - Only ON when needed
• Extensive planning required - Inflexible and Static.
• Not built for Cloud.
• Need Hadoop experts to install, maintain and use.
• High TCO - Always ON

6. Qubole UI via
Browser
SDK
ODBC
User Access
Qubole’s
AWS Account
Customer’s AWS Account
REST API
(HTTPS)
SSH
Ephemeral Hadoop Clusters,
Managed by Qubole
Slave
Master
Data Flow within
Customer’s AWS
(optional)
Other RDS,
Redshift
Ephemeral
Web Tier
Web Servers
Encrypted
Result Cache
Encrypted
HDFS
Slave
Encrypted
HDFS
RDS – Qubole
User, Account
Configurations
(Encrypted
credentials
Amazon S3
No HDFS Load
w/S3 Server Side
Encryption
Default Hive
Metastore
Encryption Options:
a) Qubole can encrypt the result cache
b) Qubole supports encryption of the ephemeral drives used for HDFS
c) Qubole supports S3 Server Side Encryption
(c)
(b)
(a)
(optional)
Custom
Hive
Metastore
SSH
BUILT FOR CLOUD PERFORMANCE COST-EFFICIENT
Ephemeral Clusters:
• Auto-Scaling - both up and down
• Spot Instances - data management and back-fill
• VMs deployed with awareness of time

7. Demo
7

8. Why Qubole?
8
“Qubole has enabled more users within Pinterest to get to the
data and has made the data platform lot more scalable and
stable”
Mohammad Shahangian - Lead, Data Science and Infrastructure
Moved to Qubole from Amazon EMR because
of stability and rapidly expanded big data usage by
giving access to data to users beyond developers.
Rapid expansion of big data beyond developers (240 users
out of 600 person company)
Use CasesUser and Query Growth
Rapid expansion in use cases ranging from ETL, search,
adhoc querying, product analytics etc.
Rock solid infrastructure sees 50% less failures as
compared to AWS Elastic Map/Reduce
Enterprise scale processing and data access

9. Why Qubole?
9
“We needed something that was reliable and easy to learn,
setup, use and put into production without the risk and high
expectations that comes with committing millions of dollars in
upfront investment. Qubole was that thing.”
Marc Rosen - Sr. Director, Data Analytics
Moved to Big data on the cloud (from internal Oracle
clusters) because getting to analysis was much
quicker than operating infrastructure themselves.
Used to answer client queries and power client
dashboards.
Use Cases# Commands Per Month
0
1250
2500
3750
5000
Aug-13
Sept-13
Oct-13
Nov-13
Dec-13
Jan-14
Feb-14
Number of queries
Segment audiences based on their behavior including
such topics as user pathway and multi-dimensional recency
analysis
Build customer profiles (both uni/multivariate) across
thousands of first party (i.e., client CRM files) and third
party (i.e., demographic) segments
Simplify attribution insights showing the effects of upper
funnel prospecting on lower funnel remarketing media
strategies