Webinar: How Banks Manage Reference Data with MongoDB

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Managing and distributing reference data globally has always been a challenge for financial institutions. Managing and maintaining database schemas while integrating and replicating that data across geographies is costly and time consuming. MongoDB's native replication capabilities and partitioned architecture make it simple to distribute and synchronize data efficiently across the globe. MongoDB’s dynamic schema dramatically reduces database maintenance for schema migrations – data structure changes can be applied with no down time, and with no impact to existing applications.

Webinar: How Banks Manage Reference Data with MongoDB

  1. 1. Managing Reference Data with MongoDB
  2. 2. Daniel Roberts Solution Architect 10gen
  3. 3. Introduction10gen is the company behind MongoDB –the leading next generation database Document- General Open- Oriented Purpose Source 3
  4. 4. MongoDB functionality MongoDB Relational Key/Value or Column Stores 4
  5. 5. Database Landscape •  No Automatic Joins •  Document Transactions •  Fast, Scalable Read/Writes 5
  6. 6. Relational Database ChallengesData Types Agile Development•  Unstructured data •  Iterative•  Semi-structured •  Short development data cycles•  Polymorphic data •  New workloadsVolume of Data New Architectures•  Petabytes of data •  Horizontal scaling•  Trillions of records •  Commodity servers•  Tens of millions of •  Cloud computing queries per second 6
  7. 7. Financial Services Use Cases1.  Risk Analysis & Reporting2.  Tick Data Capture & Analysis3.  Portfolio and P&L Reporting4.  Product Catalog and Trade Lifecycle Management5.  Trade Repository6.  Quantitative Analysis & Automated Trading7.  Order Capture8.  Reference Data 7
  8. 8. Reference Data•  How do you globally distribute reference data? –  Polymorphic data •  Price / Products / Securities Master •  Counterparty information - KYC •  Corporate Actions •  Golden / Single source truth –  Often changing in structure, •  e.g. new products –  Often High volume•  How is this typically solved today? 8
  9. 9. Current Implementations•  What do reference data solutions look like today?•  Storage –  Relational Database or Caching Technologies•  Replication –  ETL or Messaging•  Complex, Costly and Brittle –  Maintenance •  schema changes •  infrastructure –  Multiple technologies 9
  10. 10. Why MongoDB?•  What features in MongoDB are ideally suited for Global replicated reference data systems? 1.  Dynamic and flexible schema 10
  11. 11. Relational: All Data is Column/Row IssID   IssuerName   PVCurrency   117883   DWS  Vietnam  Fund   USD   69461   Independence  III  Cdo  Ltd   USD   102862   Zamano  Plc   EUR   73277   Green  Way   BMD   65134   First  European  Growth  Inc.   CHF   SecID   EventID   Company_Mee9ng   IssID   762288   407341   AGM   117883   81198   243459   SDCHG   69461   422999   410626   AGM   102862   422999   243440   SDCHG   102862   75128   20056   ISCHG   65134   11
  12. 12. Instead Match the Data in yourApplicationRelational MongoDB {! !"IssID" : 65134,! !"IssuerName" : "First European ! ! ! ! !Growth Inc.",! !"actions" : [! ! !{! ! ! !"Company_Meeting" : "ISCHG",! ! ! !"EventID" : 20056,! ! ! !"SecID" : 75128! ! !},! ! !{! ! ! !"Company_Meeting" : "LSTAT",! ! ! !"EventID" : 2716296,! ! ! !"SecID" : 75128! ! !}! !]! }! 12
  13. 13. Benefits of MongoDB’s Document Model•  Expressiveness  of  Data  Modeling   –  A  single  document  can  express  and  encompass  a  wide  variety  of  noTons  •  Flexible  Modeling   –  No  need  to  migrate  for  simple  extensions  •  Simplifica9on  of  Data  Modeling   –  Fewer  collecTons  as  most  data  can  be  encapsulated  in  a  single  document  •  Easier  Development   –  Developers  understand  documents  as  it  maps  well  to  their  data  structures  •  Faster  Time  to  Market   –  Agile  development  means  faster  results   And  enables  beEer  data  locality  =>  faster  performance  and  scaling   13
  14. 14. Why MongoDB?•  What features in MongoDB are ideally suited for Globally replicated reference data systems? 1.  Dynamic and flexible schema 2.  Built in replication and high availability 14
  15. 15. High Availability•  Automated replication and failover•  Multi-data center support•  Improved operational simplicity (e.g., HW swaps)•  Data durability and consistency 15
  16. 16. Global Replication 16
  17. 17. Why MongoDB?•  What features in MongoDB are ideally suited for Globally replicated reference data systems? 1.  Dynamic and flexible schema 2.  Built in replication and high availability 3.  Tag Aware Sharding (Geo) 17
  18. 18. MongoDB Sharding 18
  19. 19. Tag Aware Sharding EMEA NA APAC 19
  20. 20. 1. Case Study: Global Broker Dealer - Reference Data Management ETL ETL ETL ETL ETLFeeds & Batch data ETL•  Pricing Source•  Accounts Master Data ETL•  Securities Master (RDBMS)•  Corporate actions Each represents •  People $ •  Hardware $ Destination •  License $ Data •  Reg penalty $ (RDBMS) •  & other downstream problems 20
  21. 21. Solution with MongoDB Real-time Real-time Real-time Real-time Real-timeFeeds & Batch data Real-time•  Pricing•  Accounts Real-time MongoDB•  Securities Master Primary•  Corporate actions Each represents •  No people $ •  Less hardware $ •  Less license $ •  No penalty $ MongoDB •  & many less Secondaries problems 21
  22. 22. Case Study: Global investment bank Distribute reference data globally in real-time for fast local accessing and querying Problem Why MongoDB Results•  Delays up to 20 hours in •  Dynamic schema •  Will save about distributing data via ETL management: update $40,000,000 in costs and•  Had to manage 20 immediately & in one penalties over 5 years distributed systems with place same data •  Greater throughput means •  Auto-replication: data charging more to internal•  Incurring regulatory distributed in real-time groups penalties from missing SLAs •  Both cache and database: •  Network and disk speed is•  Stale data caused cache always up-to-date the bottleneck, not operational issues software and applications •  Simple data modeling & analysis: easy changes and understanding 22
  23. 23. Summary•  Why MongoDB for Reference Data solutions? 1.  Dynamic and flexible schema 2.  Built in replication and high availability 3.  Tag Aware Sharding (Geo) 23
  24. 24. Q&AUp And ComingFS webinar in April - Tick database•  http://www.10gen.com/webinar/using-mongodb-as-tick-databaseFS webinar in April - Risk•  http://www.10gen.com/webinar/mitigate-risk-with-mongodbMongoDB Days - London, San Francisco, and NYC•  http://www.10gen.com/eventsMongoDB 2.4 Release•  http://www.mongodb.org/downloads
  25. 25. Key Features JSON Data Model with Auto-Sharding for Dynamic Schema Horizontal Scalability Rich, Document-Based Flexible, Full Index Support Queries Built-In Replication and Fast, In-Place Updates High Availability Aggregation Framework and GridFS for Large File Storage Map/Reduce 25
  26. 26. For More Information Resource User Data Management Location MongoDB Downloads www.mongodb.org/download Free Online Training education.10gen.com Webinars and Events www.10gen.com/events White Papers www.10gen.com/white-papers Customer Case Studies www.10gen.com/customers Presentations www.10gen.com/presentations Documentation docs.mongodb.org Additional Info info@10gen.com 26

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