Cloud expo june 2013: Building a Real Time Analytics Platform on Big Data in the Cloud

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Building a Real Time Analytics Platform on
Big Data in the Cloud

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Cloud expo june 2013: Building a Real Time Analytics Platform on Big Data in the Cloud

  1. 1. 1Building a Real Time Analytics Platform onBig Data in the CloudSanjay SharmaPrincipal ArchitectJune 12 2013
  2. 2. Impetus©  2013  Impetus  Technologies  •  Software Solutions and Services Company•  Leader in Innovation led Technology services•  17 years of customer success, 1500 people•  Big Data, Enterprise Mobility,Test andPerformance Engineering, Carrier Grade LargeSystems
  3. 3. ©  2013  Impetus  Technologies  ?  Why  s9ll  Batch?  $$$  Credits  *  hAp://thenextweb.com/insider/2013/02/07/mailboxs-­‐user-­‐access-­‐queue-­‐is-­‐a-­‐work-­‐of-­‐frustra9ng-­‐genius/  **  hAp://en.wikipedia.org/wiki/Moores_law  Batch  to  Real  Time  Now  is  the  Time  
  4. 4. ©  2013  Impetus  Technologies  OLTP  Online  Transacons  Processing  NOW  OLAP/DW  Online  Analycal  Processing/DW  ZZZZZZZZZ…  Transac9ons  &  Analy9cal  Processing  Now  is  the  Time  
  5. 5. ©  2013  Impetus  Technologies  Age  of  Horizontal  Scalability  -­‐Divide  and  Conquer  Online  Transacons  Processing  Online  Analycal  Processing/  DW  OLTP   OLAP  
  6. 6. ©  2013  Impetus  Technologies  Online  Transac9ons  Processing  Online  Analy9cal  Processing/  DW  On  Demand  Scalability  -­‐CLOUD  OLTP   OLAP  
  7. 7. ©  2013  Impetus  Technologies  State  of  Play:  Analy9cs/  BI  Database  RESULTS  Time   Time  Ingest/ETL   SQL  Machine  Data  
  8. 8. ©  2013  Impetus  Technologies  Faster  Analy9cs:  Streaming  Analy9cs/    Complex  Event  Processing  Database   RESULTS  Time   Time  RESULTS  Ingest/ETL   SQL  Approach  1  
  9. 9. ©  2013  Impetus  Technologies  Faster  Analy9cs:  In-­‐memory  Analy9cs    Database   RESULTS  Time   Time  RESULTS  Ingest/ETL   SQL  Approach  2  
  10. 10. •  Streaming/CEP Analytics–  Storm by Twitter–  Spark Streaming by Berkley Amplabs–  IBM Streams–  SQLstream–  MS StreamInsight–  StreamBase–  Oracle CEP/Streams–  Esper©  2013  Impetus  Technologies  •  In-Memory Analytics–  SAP Hana–  Oracle Exalytics–  SAS in-memory analytics–  MS PowerpivotSome  Real  Time  So_ware  
  11. 11. ©  2013  Impetus  Technologies  •  Others–  NoSQL databases•  Cassandra, MongoDB, HBase–  Grid solutions–  MPP and NewSQL–  Druid, Kognitio–  Solr/Elastic Search/Marklogic–  Splunk–  BI products with OLAP•  Hadoop based–  Summarization/ cubepreparation engine–  Impala/Stinger/Hawq/Drill–  HstreamingSome  Real  Time  So_ware  •  Specialized–  Hardware accelerators / GPUcards•  Sisense
  12. 12. ©  2013  Impetus  Technologies  Real  Time  Analy9cs  Strategy      -­‐Key  Components  RESULTS  Ingest   SQL  Machine  Data  OLTP  OLAP/DW  ETL  Discovery& SearchDeeperAnalyticsStreamingAnalyticsReal timeAnalytics
  13. 13. ©  2013  Impetus  Technologies    NoSQL  +  Search  Machine  Data  Real  Time  Analy9cs  Strategy        -­‐Big  Data  Reference  Architecture  Example  
  14. 14. ©  2013  Impetus  Technologies  Real  Time  Analy9cs  Strategy        -­‐Data  Inges9on/  Streaming  –  Customer  Example  Machine  Data  Inges9on  Engine  (Real  9me  +  Batch  components)  Real  Time  Processing  Engine  (CEP/Analy9cs/  Rule  Engine)  Real  Time  Data  Storage  Engine  (Store  +  Indexing/Search)  Business  Process  Engine  (Business  Process/  Rule  management)  Kafa  Storm  +  Esper  HBase+  Solr  JBoss  Drools/jBPM  
  15. 15. ©  2013  Impetus  Technologies    NoSQL  +  Search  Machine  Data  Real  Time  Analy9cs  Strategy        -­‐Big  Data  Reference  Architecture  Example  
  16. 16. Impetus provides vendor-neutral Consulting &Services for Big Data AnalyticsWe take enterprises through the journey ofsuccessful Big Data adoptionWe deliver: Low-risk acceleration toBusiness value at moderate cost©  2013  Impetus  Technologies  Impetus
  17. 17. Q&Aimpetus.combigdata@impetus.comBooth# 120©  2013  Impetus  Technologies  

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