Teradata QueryGrid to MongoDB Lightning Introduction

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    11-Aug-2015
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Transcript of Teradata QueryGrid to MongoDB Lightning Introduction

  1. 1. Teradata QueryGrid to MongoDB Lightning Introduction Rich Charucki - Teradata
  2. 2. 2 What is a Teradata Data Warehouse? Analytic database In-memory, in-database Scale-out MPP 30+ petabyte sites 35PB, 4096 cores Self service BI Dashboards, reports, OLAP Predictive analytics Complex SQL 20-50 way joins 350 pages of SQL Real time access/load Mixed workloads Data scientists Power users Sales, partners 1024 nodes Intel CPUs 512GB Intel CPUs 512GB Intel CPUs 512GB Intel CPUs 512GB
  3. 3. 3 JSONPath inside SQL Color Size Prod_ID Create_Time ----- ----- ------- ------------------- Blue Small 96 2013-06-17 20:07:27 SELECT box.MFG_Line.Product.Color AS "Color", box.MFG_Line.Product.Size AS "Size", box.MFG_Line.Product.Prod_ID AS "Prod_ID", box.MFG_Line.Product.Create_Time AS "Create_Time" FROM mfgTable WHERE CAST(box.MFG_Line.Product.Create_Time AS TIMESTAMP) >= TIMESTAMP'2013-06-16 00:00:00' AND box.MFG_Line.Product.Prod_ID = 96;
  4. 4. 4 Math and Stats Data Mining Business Intelligence Applications Languages Marketing ANALYTIC TOOLS & APPS USERS UNIFIED DATA ARCHITECTURE Marketing Executives Operational Systems Frontline Workers Customers Partners Engineers Data Scientists Business Analysts INTEGRATED DATA WAREHOUSE DISCOVERY PLATFORM DATA LAKE REAL TIME PROCESSINGERP SCM CRM Images Audio and Video Machine Logs Text Web and Social SOURCES
  5. 5. 5 MONGODB NoSQL Database Teradata and MongoDB: QueryGrid IDW TERADATA DATABASE Discovery ASTER DATABASE Business users Data scientists TERADATA ASTER SQL, SQL-MR, SQL-GR Teradata Systems TERADATA DATABASE HADOOP Push-down to Hadoop SAS, Perl, R, Python, Ruby LANGUAGES
  6. 6. 6 Integration Export / Import Direct Connect
  7. 7. 7 Teradata and MongoDB Operational + Analytical Rich MongoDB applications Rich Teradata analytics Complementary Teradata pulls directly from MongoDB sharded clusters Teradata pushes back to MongoDB deployments MongoDB Teradata Operational Data Analytics
  8. 8. 8 Scale-out NoSQL + Scale-out DW SQL Application Primary Shard 1 Primary Shard 2 Primary Shard N Primary Shard 3 Query router Query router Query router NoSQL SQL AMPAMP PE AMPAMP PE AMPAMP PE AMPAMP PE
  9. 9. 9 Query Router Shard 1 Shard 2 Shard 3 Shard 4 Contract Phase Teradata node PE SQL E A H AMP AMP AMP AMP
  10. 10. 10 Contract Phase Teradata node AMP AMP AMP AMP E A H Query Router Shard 1 Shard 2 Shard 3 Shard 4 PE
  11. 11. 11 Data Export to Shards Teradata node E A H Query Router Shard 1 Shard 2 Shard 3 Shard 4 AMP AMP AMP AMP PE
  12. 12. 12 Import Data from Shards Teradata node E A H Query Router Shard 1 Shard 2 Shard 3 Shard 4 AMP AMP AMP AMP PE
  13. 13. 13 Back-office context to the Front-office operations Use cases
  14. 14. 14 Data Warehouse eCommerce in Action: A Virtuous Circle Buyer preferences Sales catalog Campaigns Recent purchases Profitability Shard Shard Shard Shard Shard Shard Shard Shard
  15. 15. 15 Data Warehouse Shard Shard Shard Shard Shard Shard Shard Shard Call Center Efficiency: A Virtuous Circle Trouble tickets Customer profiles Payment history Claims Next best offer web logs
  16. 16. 16 Context from the DW Enriching MongoDB applications Integration Import/export Teradata QueryGrid Two scale out architectures OLTP scale-out Analytics scale-out JSON in the data warehouse Conclusions
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