With more and more data being generated and stored in the cloud, you need a modern data platform that can extend to any environment so you can derive value from all your data. Cloudera Enterprise is the leading enterprise Hadoop platform for cloud deployments. It’s the easiest way to manage and secure Hadoop data across any cloud environment and includes component-level support for cloud-native object stores. This makes the platform uniquely suited to handle transient jobs like ETL and BI analytics, as well as persistent workloads like stream processing and advanced analytics. With the recent release of Cloudera 5.8, Apache Impala (incubating) has added support for Amazon S3, enabling business analysts to get instant insights from all data through high-performance exploratory analytics and BI. 3 Things to learn: Join David Tishgart, Director of Product Marketing, and James Curtis, Senior Analyst Data Platforms & Analytics at 451 Research, as they discuss: * Best practices for analytic workloads in the cloud
 * A live demo and real-world use cases
 * What’s next for Cloudera and the cloud


1. 1© Cloudera, Inc. All rights reserved.
High-Performance Analytics in
the Cloud with Apache Impala
James Curtis | Sr. Analyst, Data Platforms & Analytics | 451 Research
David Tishgart | Cloud Product Marketing | Cloudera
Tom Deane | Cloud Product Management | Cloudera

2. 2© Cloudera, Inc. All rights reserved.
David Tishgart
Director of Product
Marketing - Cloud
Cloudera
Jim Curtis
Senior Analyst Data
Platforms & Analytics
451 Research
Tom Deane
Senior Product
Manager - Cloud
Cloudera
Today’s Speakers

3. 3© Cloudera, Inc. All rights reserved.
Agenda
1. Hadoop in the cloud
2. Why users migrate to the cloud for big data analytics
3. Cloud considerations
4. Cloudera Enterprise for cloud-based analytics
5. Product Demo
6. Q&A

4. 451 Research is a leading IT research & advisory company
4
Founded in 2000
250+ employees, including over 100 analysts
1,000+ clients: Technology & Service providers, corporate
advisory, finance, professional services, and IT decision makers
50,000+ IT professionals, business users and consumers in our research
community
Over 52 million data points published each quarter and 4,500+ reports
published each year
2,000+ technology & service providers under coverage
451 Research and its sister company, Uptime Institute, are the two divisions
of The 451 Group
Headquartered in New York City, with offices in London, Boston, San
Francisco, Washington DC, Mexico, Costa Rica, Brazil, Spain, UAE, Russia,
Taiwan, Singapore and Malaysia
Research & Data
Advisory
Events
Go 2 Market

5. Total Hadoop Revenue
5
Source: 451 Research Market Monitor Total Data Service
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
$4,000
$4,500
$5,000
2015 2016 2017 2018 2019 2020
$inM
42% CAGR expected for Hadoop-aaS
39% CAGR expected for total Hadoop market
© 2016 451 Research. All rights reserved
Hadoop Vendors
Altiscale Dremio Pivotal
Amazon Web Services Esgyn Qubole
BlueData Hortonworks Rackspace
Cazena IBM Splice Machine
CenturyLink JethroData Stratio
Cloudera MapR Technologies Teradata
Cray MetaScale Tonomi
Data Artisans Microsoft Treasure Data
Databricks Oracle VMware
Doopex Pepperdata WANdisco

6. Data Gravity: Play It as It Lies
Cloud Compute
 In golf, the USGA Rule 13 states that ‘the ball must be played where it lies….’
 Data gravity: data being analyzed where it resides
(instead of moving the data to a data warehouse for analysis)
 Our research shows 33% of IT storage professionals already use cloud storage services
and 23.4% plan to purchase cloud services in next 90 days
Source: 451 Research, Voice of Enterprise Storage, Q1 2016.

7. Public Cloud Infrastructure (IaaS, PaaS) Storage Growth
Cloud Compute
Source: 451 Research, Voice of the Enterprise Storage, Q1 2016.
Database/DW – Today
Database/DW – 2 Yrs.
Data Analytics/BI – Today
Data Analytics/BI – 2 Yrs.
Big Data – Today
Big Data – 2 Yrs.
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

8. Why Use Cloud for Analytics/BI and Big Data?
Source: 451 Research, Voice of the Enterprise Cloud, Workloads, and Key Projects 2016.
Analytics/BI Workloads Big Data Workloads

9. Benefits—Moving Analytic Workloads to Cloud Storage
 Financial—costs significantly less to store data in S3 (AWS) over HDFS running on EC2 (AWS)
HDFS requires three copies of each block, whereas cloud storage uses auto backups and
compression
 Scalability
— HDFS inherently scales; it requires manual configuration and management. Cloud storage
automatically scales as data is added, requiring no user involvement
— Ability to scale storage and compute separately, based on use case and need
 Durability/Persistence—with HDFS on EC2, data is persisted for the life of the instance. Cloud
storage is designed to deliver data durability to 99.9999%

10. Considerations: Leveraging the Cloud for Analytics
Cloud Compute
 Remember data gravity. It’s much easier to analyze the data where it resides, particularly if
it’s in the cloud
 If moving to the cloud, know why and what you’re getting into. If data is on premise and
you move it to the cloud, then keep it in cloud
 Because cloud storage separates storage from compute (versus local storage),
performance may be impacted
 When moving objects to cloud storage, be aware size limitations for objects
 Cloud providers enable security but organizations will want to implement platform-level
security as well
 Avoid looking at cloud or cloud storage from a single benefit. Does it benefit the
organization across multiple dimensions?
 It’s not necessarily an either/or proposition. It’s acceptable for enterprises to run a mix of
cloud, cloud storage, and on-premises

11. Thank You!
james.curtis@451research.com
www.451research.com

12. 12© Cloudera, Inc. All rights reserved.
Cloud growth fueling Hadoop use cases
Requirements to move from POCs
to enterprise use cases
- Security
- Portability
- Flexibility
- Ecosystem support

13. 13© Cloudera, Inc. All rights reserved.
Common workloads in the cloud
Only pay for what you need,
when you need it
▪ Transient clusters
▪ Elastic workload
▪ Object storage centric
▪ Cloud-native deployment
ETL/Modeling
(Data Engineering)
App Delivery
(Operational
Database)
Reduce Operating Costs New Insights, New Revenue Run Without Risk
BI/Analytics
(Analytic Database)
Explore and analyze all data,
wherever it lives
▪ Transient or Persistent clusters
▪ Sized to demand
▪ HDFS or object storage
▪ Lift-and-shift or cloud-native
deployment
Enterprise-grade to protect
your business, no matter what
▪ Fixed clusters
▪ Periodic sync
▪ All HDFS storage
▪ Lift-and-shift deployment

14. 14© Cloudera, Inc. All rights reserved.
Lift and Shift for long-running
workloads
Cloud-native for transient
clusters
Deployment Models in the Cloud
Object Store

15. 15© Cloudera, Inc. All rights reserved.
Apache Impala: Self-Service BI & Exploratory Analytics
• Self-Service Data Agility
• No rigid data modeling encumbrances for agile acquisition
• Iteratively analyze and flexibly model
• Self-Service Exploratory Analytics
• Interactive responses for iterative exploration
• Confidently handle all BI and SQL users
• Cost-Effective Scalability with Users/Data
• Easily add nodes to handle more data and users
• Leverage the full potential of available data
• Productively Use Existing Tools and Skills
• Integration with all leading BI tools & compatible analytic
SQL language
• Metadata and lineage for easy data discovery
• Intelligent SQL editor for greater developer productivity

16. 16© Cloudera, Inc. All rights reserved.
Deploy on any cloud infrastructure
Cloudera Director: Management for IaaS-related and CDH cluster operations
Easy Administration
• Dynamic cluster lifecycle management
• Single pane of glass: multi-cluster view
• Consumption based billing and metering
Enterprise-grade
• Integration across Cloudera Enterprise
• Management of CDH deployments at
scale
Flexible Deployments
• No cloud vendor lock-in: open plugin
framework for IaaS platforms
• Scaling of provisioned clusters
• Spot instance provisioning
Cloudera Director

17. 17© Cloudera, Inc. All rights reserved.
Cloudera’s Analytic Database Solution
OPERATIONS
DATAMANAGEMENT
UNIFIED SERVICES
PROCESS,ANALYZE, SERVE
STORE
INTEGRATE
Identify, offload, &
optimize workloads to
Hadoop
Navigator
Optimizer
Intelligent SQL editor
Hue
Audit, lineage,
encryption, key
management, & policy
lifecycles
Navigator
Integration with the
leading BI tools
BI Partners
Interactive query engine
for BI & SQL analytics
Impala
Large-scale ETL & batch
processing engine
Hive-on-
Spark
Multi-Storage, Multi-Environment

18. 18© Cloudera, Inc. All rights reserved.
Impala Key Cloud Benefits vs Cloud Analytic Database
• Cloud Elasticity
• Ability to grow/shrink cluster sizes (native architecture)
• Elastic compute scale (via direct query from S3)
• Transient workloads (via direct query from S3)
• Data Agility
• Faster, more agile data acquisition
• Data portability – open formats and open storage (even more so with S3)
• Scalability
• Proven through hundreds of nodes
• Proven with high concurrency
• Hybrid cloud
• Runs across clouds and on-prem
• Runs across S3, HDFS, Kudu, Isilon, DSSD, etc

19. 19© Cloudera, Inc. All rights reserved.
Demo – Impala on S3
Real-time SQL analytics with Cloudera Enterprise deployed
on Amazon Web Services

20. 20© Cloudera, Inc. All rights reserved.
Why Impala on S3?
• Decouple storage from compute
• Save on storage costs and replication costs
• Pay-per-use (provision, grow, shrink, and terminate clusters)
• No need to migrate data out of S3 to another filesystem

21. 21© Cloudera, Inc. All rights reserved.
Impala on S3 Scalability
2.1x speedup for 4% lower cost for multi-user
For full details:
http://blog.cloudera.com/blog/2016/08/analytics-and-bi-on-amazon-s3-with-apache-impala-incubating/

22. 22© Cloudera, Inc. All rights reserved.
End-to-End Demo

23. 23© Cloudera, Inc. All rights reserved.
Why Cloudera in the Cloud?
Hadoop Expertise
◆ Most committers
◆ World-class innovation
◆ Enterprise-class stack
◆ Granular data security +
governance
◆ Best support, services, training
Flexible Deployments
◆ No vendor lock-in
◆ Multi-cloud and on-prem
◆ Transient and long-lived
clusters
Customer success – not
cloud consumption
◆ Focus on infrastructure choice
◆ Security separation from
infrastructure leads to reduced
risk
Flexible Pricing
◆ Pay-as-you-go cloud usage
◆ Traditional node-based
licensing

24. 24© Cloudera, Inc. All rights reserved.
Get started with Cloudera Enterprise in the cloud
Deploy and manage Cloudera
Enterprise on AWS, GCP, Azure
or the cloud of your choice
Deploy an enterprise data hub
on AWS
Provision and deploy Cloudera
Enterprise on the Azure
Marketplace
Cloudera Director AWS Quickstart Azure Marketplace

25. 25© Cloudera, Inc. All rights reserved.
Q&A

26. 26© Cloudera, Inc. All rights reserved.
Thank You