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Big Data Integration: 
Why Same Old, Same Old Won't Cut It
Today’s Agenda 
• Discussion with Greg Benson - Big Data Integration: Why Now? 
• SnapLogic Introduction: SnapReduce and the Hadooplex 
• SnapLogic Elastic Integration Demonstration 
• Discussion 
Darren Cunningham 
VP of Marketing 
Craig Stewart 
Sr. Director 
Product Management 
Greg Benson 
Chief Scientist
About Greg Benson 
• SnapLogic Chief Scientist 
• Professor of Computer 
Science at the University of 
San Francisco 
• Worked on research in distributed systems, parallel programming, 
OS kernels, and programming languages for the last 20 years
Big Data Primer: What is Hadoop 2.0?
Big Data Integration: 
Why Now? What’s Different
What Do You Hear from Customers?
SnapLogic: Connecting Data, Apps and APIs 
Our unified platform significantly speeds up 
enterprise data access everywhere. 
- Gaurav Dhillon, SnapLogic Founder and CEO 
• Experienced Team: Leadership from Informatica, 
Salesforce, Microsoft 
• Headquarters: San Mateo, CA 
• Investors: Andreessen Horowitz & Ignition 
• Advisory Board: AstraZeneca, HP, Symantec, Yahoo 
• Customers: Adobe, Acxiom, Blackberry, Bloomin’ 
Brands, CapitalOne, Cisco, GE, iRobot, Netflix…
Elastic Integration Platform as a Service 
Integration Cloud! 
Designer, Manager, Dashboards 
(Multi-tenant cloud service) 
Elastic Execution! 
Snaplex 
Snaps! 
(Buy or Build) 
“Cloudplex” 
“Hadooplex” 
“Groundplex”
Hybrid Deployment 
• Streams: No data is 
stored/cached 
• Secure: 100% 
standards-based 
• Elastic: Scales out & 
handles data and app 
integration use cases 
Metadata 
Data
Elastic Scale Out 
• Each Snaplex can 
elastically expand 
and contract based 
on data traffic 
flowing through it 
• Built-in smarts to 
automatically scale 
the Snaplex out and 
in to handle variable 
traffic loads
SnapLogic for Big Data Integration 
ACQUIRE PREPARE DELIVER 
• Sort 
• Aggregate 
• Join 
• Merge 
• Transform 
Hadoop + SnapReduce
SnapReduce and the Hadooplex 
Acquire, Prepare, Deliver Big Data 
YARN 
YARN 
MapReduce 
MapReduce 
MapReduce 
MapReduce 
MapReduce 
MapReduce 
MapReduce 
MapReduce 
Snaplex YARN Application! 
MapReduce Generation! 
Snaplogic iPaaS + Hadoop 
= Snaplex Container
Hadooplex: Snaplex YARN Application 
= Snaplex Container 
• Snaplex has 3 types: 
o Cloudplex 
o Groundplex 
o Hadooplex 
• Kerberos 
Authentication 
• Certified by 
Cloudera and 
Hortonworks
SnapReduce: Pipelines Generate MapReduce 
SnapReduce 
Compiler 
MAP MAP MAP MAP 
REDUCE MAP REDUCE MAP 
Map Reduce 
• A checkbox option to 
SnapReduce-enable a 
pipeline 
• New support for 
SequenceFile, RCFile, 
document (JSON) 
processing for 
MapReduce jobs 
YARN
Big Data Integration Demonstration
What’s Next?
Discussion 
@SnapLogic 
Facebook.com/SnapLogic 
Plus.google.com/+SnapLogic

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Webinar: Big Data Integration - Why Same Old, Same Old Won't Cut It

  • 1. Big Data Integration: Why Same Old, Same Old Won't Cut It
  • 2. Today’s Agenda • Discussion with Greg Benson - Big Data Integration: Why Now? • SnapLogic Introduction: SnapReduce and the Hadooplex • SnapLogic Elastic Integration Demonstration • Discussion Darren Cunningham VP of Marketing Craig Stewart Sr. Director Product Management Greg Benson Chief Scientist
  • 3. About Greg Benson • SnapLogic Chief Scientist • Professor of Computer Science at the University of San Francisco • Worked on research in distributed systems, parallel programming, OS kernels, and programming languages for the last 20 years
  • 4. Big Data Primer: What is Hadoop 2.0?
  • 5. Big Data Integration: Why Now? What’s Different
  • 6. What Do You Hear from Customers?
  • 7. SnapLogic: Connecting Data, Apps and APIs Our unified platform significantly speeds up enterprise data access everywhere. - Gaurav Dhillon, SnapLogic Founder and CEO • Experienced Team: Leadership from Informatica, Salesforce, Microsoft • Headquarters: San Mateo, CA • Investors: Andreessen Horowitz & Ignition • Advisory Board: AstraZeneca, HP, Symantec, Yahoo • Customers: Adobe, Acxiom, Blackberry, Bloomin’ Brands, CapitalOne, Cisco, GE, iRobot, Netflix…
  • 8. Elastic Integration Platform as a Service Integration Cloud! Designer, Manager, Dashboards (Multi-tenant cloud service) Elastic Execution! Snaplex Snaps! (Buy or Build) “Cloudplex” “Hadooplex” “Groundplex”
  • 9. Hybrid Deployment • Streams: No data is stored/cached • Secure: 100% standards-based • Elastic: Scales out & handles data and app integration use cases Metadata Data
  • 10. Elastic Scale Out • Each Snaplex can elastically expand and contract based on data traffic flowing through it • Built-in smarts to automatically scale the Snaplex out and in to handle variable traffic loads
  • 11. SnapLogic for Big Data Integration ACQUIRE PREPARE DELIVER • Sort • Aggregate • Join • Merge • Transform Hadoop + SnapReduce
  • 12. SnapReduce and the Hadooplex Acquire, Prepare, Deliver Big Data YARN YARN MapReduce MapReduce MapReduce MapReduce MapReduce MapReduce MapReduce MapReduce Snaplex YARN Application! MapReduce Generation! Snaplogic iPaaS + Hadoop = Snaplex Container
  • 13. Hadooplex: Snaplex YARN Application = Snaplex Container • Snaplex has 3 types: o Cloudplex o Groundplex o Hadooplex • Kerberos Authentication • Certified by Cloudera and Hortonworks
  • 14. SnapReduce: Pipelines Generate MapReduce SnapReduce Compiler MAP MAP MAP MAP REDUCE MAP REDUCE MAP Map Reduce • A checkbox option to SnapReduce-enable a pipeline • New support for SequenceFile, RCFile, document (JSON) processing for MapReduce jobs YARN
  • 15. Big Data Integration Demonstration
  • 17. Discussion @SnapLogic Facebook.com/SnapLogic Plus.google.com/+SnapLogic

Notes de l'éditeur

  1. http://datascience.berkeley.edu/what-is-big-data/
  2. The unit of scalability inside Snaplex is a JVM. Each Snaplex is initialized with a preconfigured number of JVMs (say one, for example). Once the utilization of that one JVM reaches a certain threshold (say 80%), a new JVM is automatically spun up to handle any additional workload. Once this excess data traffic has been processed and the second JVM is sitting idle, it gets torn down to scale back in to its original size.”
  3. Magnify the containers? May it magnify out.