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Managing Reference Data
      with MongoDB
Daniel Roberts
  Solution Architect
        10gen
Introduction

10gen is the company behind MongoDB –
the leading next generation database




 Document-         General               Open-
  Oriented         Purpose              Source



                      3
MongoDB functionality


                        MongoDB




 Relational




                             Key/Value or
                             Column Stores




                 4
Database Landscape
                     •  No Automatic Joins
                     •  Document Transactions
                     •  Fast, Scalable Read/Writes




                5
Relational Database Challenges
Data Types                    Agile Development
•  Unstructured data          •  Iterative
•  Semi-structured            •  Short development
   data                          cycles
•  Polymorphic data           •  New workloads




Volume of Data                New Architectures
•  Petabytes of data          •  Horizontal scaling
•  Trillions of records       •  Commodity servers
•  Tens of millions of        •  Cloud computing
   queries per second



                          6
Financial Services Use Cases

1.  Risk Analysis & Reporting
2.  Tick Data Capture & Analysis
3.  Portfolio and P&L Reporting
4.  Product Catalog and Trade Lifecycle Management
5.  Trade Repository
6.  Quantitative Analysis & Automated Trading
7.  Order Capture
8.  Reference Data



                                7
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
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
Why MongoDB?

•  What features in MongoDB are ideally suited for
   Global replicated reference data systems?

  1.  Dynamic and flexible schema




                          10
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
Instead Match the Data in your
Application
Relational             MongoDB
                  {!
                       !"IssID" : 65134,!
                       !"IssuerName" : "First European
                       !   !    !   !   !Growth Inc.",!
                       !"actions" : [!
                       !     !{!
                       !     !    !"Company_Meeting" : "ISCHG",!
                       !     !    !"EventID" : 20056,!
                       !     !    !"SecID" : 75128!
                       !     !},!
                       !     !{!
                       !     !    !"Company_Meeting" : "LSTAT",!
                       !     !    !"EventID" : 2716296,!
                       !     !    !"SecID" : 75128!
                       !     !}!
                       !]!
                  }!


                  12
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
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
High Availability




•  Automated replication and failover
•  Multi-data center support
•  Improved operational simplicity (e.g., HW swaps)
•  Data durability and consistency

                               15
Global Replication




                 16
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
MongoDB Sharding




              18
Tag Aware Sharding


                EMEA
           NA




                       APAC




                19
1. Case Study: Global Broker Dealer -
     Reference Data Management

                                          ETL
                                                  ETL

                                                   ETL             ETL




                                                             ETL

Feeds & 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
Solution with MongoDB

                                       Real-time
                                                       Real-time

                                                         Real-time           Real-time




                                                                     Real-time

Feeds & 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
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
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
Q&A
Up And Coming

FS webinar in April - Tick database
•  http://www.10gen.com/webinar/using-mongodb-as-tick-database

FS webinar in April - Risk
•  http://www.10gen.com/webinar/mitigate-risk-with-mongodb

MongoDB Days - London, San Francisco, and NYC
•  http://www.10gen.com/events

MongoDB 2.4 Release
•  http://www.mongodb.org/downloads
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
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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Webinar: How Banks Manage Reference Data with MongoDB

  • 1. Managing Reference Data with MongoDB
  • 2. Daniel Roberts Solution Architect 10gen
  • 3. Introduction 10gen is the company behind MongoDB – the leading next generation database Document- General Open- Oriented Purpose Source 3
  • 4. MongoDB functionality MongoDB Relational Key/Value or Column Stores 4
  • 5. Database Landscape •  No Automatic Joins •  Document Transactions •  Fast, Scalable Read/Writes 5
  • 6. Relational Database Challenges Data Types Agile Development •  Unstructured data •  Iterative •  Semi-structured •  Short development data cycles •  Polymorphic data •  New workloads Volume 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. Financial Services Use Cases 1.  Risk Analysis & Reporting 2.  Tick Data Capture & Analysis 3.  Portfolio and P&L Reporting 4.  Product Catalog and Trade Lifecycle Management 5.  Trade Repository 6.  Quantitative Analysis & Automated Trading 7.  Order Capture 8.  Reference Data 7
  • 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. 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. Why MongoDB? •  What features in MongoDB are ideally suited for Global replicated reference data systems? 1.  Dynamic and flexible schema 10
  • 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. Instead Match the Data in your Application Relational 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. 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. 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. High Availability •  Automated replication and failover •  Multi-data center support •  Improved operational simplicity (e.g., HW swaps) •  Data durability and consistency 15
  • 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
  • 19. Tag Aware Sharding EMEA NA APAC 19
  • 20. 1. Case Study: Global Broker Dealer - Reference Data Management ETL ETL ETL ETL ETL Feeds & 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. Solution with MongoDB Real-time Real-time Real-time Real-time Real-time Feeds & 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. 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. 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. Q&A Up And Coming FS webinar in April - Tick database •  http://www.10gen.com/webinar/using-mongodb-as-tick-database FS webinar in April - Risk •  http://www.10gen.com/webinar/mitigate-risk-with-mongodb MongoDB Days - London, San Francisco, and NYC •  http://www.10gen.com/events MongoDB 2.4 Release •  http://www.mongodb.org/downloads
  • 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. 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