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MongoDB for Oracle Experts - OUGF Harmony 2014

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A lightweight MongoDB introduction presented to some of the most senior Oracle experts in the Nordics.

A lightweight MongoDB introduction presented to some of the most senior Oracle experts in the Nordics.

Published in: Technology

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Transcript

  • 1. MongoDB The Database for Modern Applications Solutions Architect, MongoDB Henrik Ingo
  • 2. 2 The 70s...
  • 3. 3 1979: Sony Walkman
  • 4. 4 1974: Post-it notes
  • 5. 5 1971: First Man on the Moon
  • 6. 6 1966: Telefax (popularized during the 70s)
  • 7. 7 1977: Apple II, the first PC
  • 8. 8 The Relational Database
  • 9. Things the RDBMS is optimized for...
  • 10. 10 Disk space
  • 11. 11 Data integrity
  • 12. 12 Waterfall Development Cycle Business Requirementss Analysis Technical Requirements DataBase Schema Design Software Development QA Production
  • 13. 13 Flexibility (seriously) /* ---------------------------------- */ /* ----- Begin the PL/SQL block ----- */ /* ---------------------------------- */ EXEC SQL EXECUTE DECLARE insufficient_funds EXCEPTION; old_bal NUMBER; min_bal CONSTANT NUMBER := 500; BEGIN SELECT bal INTO old_bal FROM accounts WHERE account_id = :acct; -- If the account doesn't exist, the NO_DATA_FOUND -- exception will be automatically raised. :new_bal := old_bal - :debit; IF :new_bal >= min_bal THEN UPDATE accounts SET bal = :new_bal WHERE account_id = :acct; INSERT INTO journal VALUES (:acct, 'Debit', :debit, SYSDATE); :status := 'Transaction completed.'; ELSE RAISE insufficient_funds; END IF; ....
  • 14. The reality in 2014...
  • 15. 15 Business logic in PL/SQL is not a best practice ?
  • 16. 16 RDBMS is a poor match to OO Relational Database Object Relational Mapping Application Code XML Config DB Schema
  • 17. 17 Document Data Model Relational MongoDB { first_name: ‘Paul’, surname: ‘Miller’, city: ‘London’, location: [45.123,47.232], cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } } }
  • 18. 18 Developers are more productive
  • 19. 19 Iterative development Business Requirementss Rapid Prototyping Review Production
  • 20. 20 Data exists in diverse sources... ...beyond our control, btw. social media sensors Legacy RDBMS Legacy RDBMS Legacy RDBMS
  • 21. Big Data?
  • 22. 22 Big Data is all about Volume Velocity Variety
  • 23. 23 You want a DB that has Volume Velocity Variety Scale-out Low latency Flexible schema
  • 24. Typical MongoDB projects for Oracle experts
  • 25. 25 Data Hub CRM CRM CRM MongoDB Dashboard
  • 26. 26 Insurance leader generates coveted 360-degree view of customers in 90 days – “The Wall” Case Problem Why MongoDB Results • No single view of customer • 145 yrs of policy data, 70+ systems, 15+ apps • 2 years, $25M trying to aggregate in RDBMS – failed • Agility – prototype in 5 days; production in 90 days • Dynamic schema & rich querying – combine disparate data into one data store • Hot tech to attract top talent • Increased call center productivity • Better customer experience, reduced churn, more upsell opps • Dozens more projects in the works to leverage this data platform
  • 27. 27 Staging hub MongoDB RDBMS systems RDBMS Staging, Data preparation DWH Graphing SW
  • 28. 28 Archive Archive App (MySQL)
  • 29. 29 Stores billions of posts in myriad formats with MongoDB Case Problem Why MongoDB Results • 1.5M posts per day, different structures • Inflexible MySQL, lengthy delays for making changes • Data piling up in production database • Poor performance • Flexible document- based model • Horizontal scalability built in • Easy to use • Interface in familiar language • Initial deployment held over 5B documents and 10TB of data • Automated failover provides high availability • Schema changes are quick and easy
  • 30. 30 Branch out MongoDB RDBMS app Original DB New functionality or Big Data