Data! Data! Data!

4394ceb8b277f35ee3da7030384efb5d?s=47 David Bonilla
November 19, 2016

Data! Data! Data!

A cosmovision of the database industry and database itself as a product, not just a technology.

4394ceb8b277f35ee3da7030384efb5d?s=128

David Bonilla

November 19, 2016
Tweet

Transcript

  1. ATA! D ATA! D ATA! D ( @david_bonilla ) #datadatadata

  2. DAVID BONILLA 39 YO FATHER OF IRENE AND DANI ATLETICO

    DE MADRID ÜBERFAN CHIEF PRODUCT MANAGER @ 8KDATA 15Y EXPERIENCE SHIPPING DIGITAL PRODUCTS
  3. AVAILABLE ON NOV 30TH Enabling SQL Analytics & Data Warehousing

    for MongoDB Your queries 100x faster. No kidding.
  4. A database is a collection of data organized with tables,

    queries, reports, views, and other objects. A database management system (DBMS) is a computer software application that interacts with the user and other applications to allow the definition, creation, querying, update, and administration of databases. database (dā-tə-ˌbās)
  5. DO WE REALLY KNOW ABOUT DATABASES?

  6. I HAVE NO FROCKING IDEA WHAT I M DOING ,

  7. None
  8. None
  9. None
  10. None
  11. JUST PROTOTYPING

  12. Database Apache Express JS Angular THE MEAN STACK

  13. Database Cordova Ionic Angular THE HYBRID MOBILE STACK

  14. Database IIS .NET ASP THE BILL STACK

  15. Database PHP THE PHP SCRIPT KIDDIE STACK

  16. Database Doctrine Symfony 2 HTML 5 THE PHP “I WANT

    TO BELIEVE” STACK
  17. Database Tomcat 4 Struts 1.2 JSP THE JAVA HARDCORE STACK

  18. Database Active Record Ruby on Rails ERB THE “I WAS

    COOL IN 2006" STACK
  19. Database Cobol THE OLD SKOOL STACK

  20. STATE OF THE ART IN DBMS

  21. None
  22. $30B AGR 6% Relational Databases $5B AGR 35% NoSQL Databases

    DBMS TAM
  23. None
  24. WHICH DBMS SHOULD I USE?

  25. TL;DR KNOW-HOW PURPOSE

  26. DBMS BY PURPOSE OLTP DATAWAREHOUSE RTA OLAP Cassandra Greenplum Data

    Warehouse
  27. CURRENT BEST PRACTICE MONOLITH MICROSERVICES POO THIS WAY

  28. POLYGLOT PERSISTENCE

  29. MICROSERVICES MAKE WORKING WITH POLYGLOT PERSISTENCE NATURAL (BUT NOT EASY).

  30. HOSTED DBMS

  31. HOSTED DBMS IaaS PaaS DBaaS Control + -

  32. Latency Security Governance Regulation THE 4 HORSEMEN OF THE HOSTED

    DBMS APOCALYPSE
  33. LATEEEEEEEEEEENCY

  34. LATEEEEEEEEEEENCY

  35. YOUR CONVENIENCE CAN’T BE EARNED IN EXCHANGE FOR YOUR SOFTWARE

    PERFORMANCE.
  36. DISTRIBUTED DBMS PICK 2 Partition Tolerance The System works well

    despite physical network partitions Availability Each client can always read and write Consistency All clients have the same view of the data (CAP THEOREM 101)
  37. DISTRIBUTED DBMS PICK 1 Availability Each client can always read

    and write Consistency All clients have the same view of the data (CAP THEOREM 101) Partition Tolerance The System works well despite physical network partitions
  38. CARLY RAE JEPSEN https://aphyr.com Hey I just met you Our

    network's crazy But here's my data So store it maybe
  39. DO YOU REALLY NEED TO SCALE HORIZONTALLY? STACK OVERFLOW SERVES

    1.3 BILLION PAGEVIEWS MONTHLY WITH 4 SQL SERVERS.
  40. MATURITY

  41. MATURITY

  42. MATURITY “Oracle was started in 1977. It wasn't until 1990

    that they had a product that they weren't embarrassed by. The first couple of versions were viewed to be a joke. MySQL was started in 1988 – it wasn't until like the early 2000s that it was viewed as a viable product.” ~ Dev Ittycheria, MongoDB CEO
  43. MATURITY

  44. a professional must focus on provide value TO CUSTOMERS not

    on being a beta tester of the last hyped technology.
  45. TAKE IT EASY

  46. TAKE IT EASY

  47. TAKE IT EASY

  48. Those who cannot remember the past are condemned to repeat

    it ~ GEORGE SANTAYANA
  49. REALITY CHECK YOU DON’T NEED TO BE WEB SCALE (FROM

    DAY 1) YOU DON’T NEED TO BUILD MICROSERVICES (FROM DAY 1) HOST YOUR DATA NEAR YOUR LOGIC EVALUATE NOT ONLY THE SYSTEM BUT ITS ECOSYSTEM DBMS SHOULD BE A FACILITATOR NOT A BOTTLENECK WHEN IN DOUBT, CHOOSE A GENERAL PURPOSE RDBSM DEFINE A BACKUP AND RESTORE POLICY (FROM DAY 1)
  50. no matter how powerful the database behind you is IF

    THE FRONT-END LOGIC SUCKS, YOUR SOFTWARE WILL SUCK.
  51. Q & A SLIDES bit.ly/datamotion16 TWITTER @david_bonilla CONTACT david@8kdata.com BLOG

    www.bonillaware.com
  52. ATA! D ATA! D ATA! D

  53. • https://en.wikipedia.org/wiki/ACID • https://hpi.de/naumann/projects/rdbms-genealogy.html • https://451research.com/state-of-the-database-landscape • http://martinfowler.com/articles/nosql-intro-original.pdf • http://db-engines.com/

    • http://www.slideshare.net/tmatyashovsky/new-life-inside-monolithic-application • http://www.slideshare.net/alvarosanchezmariscal/stateless-authentication-for-microservices • http://www.mongodb-is-web-scale.com/ • http://robertgreiner.com/2014/08/cap-theorem-revisited/ • https://en.wikipedia.org/wiki/CAP_theorem • https://en.wikipedia.org/wiki/Paxos_(computer_science) • https://aphyr.com/tags/Jepsen • http://queue.acm.org/detail.cfm?id=1394128 • http://www.informationweek.com/database/the-man-who-tortures-databases/d/d-id/1111407 • https://www.infoq.com/news/2015/06/scaling-stack-overflow • http://nickcraver.com/blog/2016/02/17/stack-overflow-the-architecture-2016-edition/ • http://stackexchange.com/performance • http://www.theregister.co.uk/2016/11/16/mongodbs_ceo/ • http://www.odbms.org/2015/07/nosql-by-the-numbers/ • https://engineering.meteor.com/mongodb-queries-dont-always-return-all-matching- documents-654b6594a827#.g0bgx1u3b • http://de.slideshare.net/felixgessert/nosql-data-stores-in-research-and-practice-icde-2016-tutorial-extended-version • https://softwareefficiency.wordpress.com/2015/03/14/big-data-technology-and-the-responsibility-shift/ • https://speakerdeck.com/abchaudhri/considerations-for-using-nosql-technology-on-your-next-it-project-1 • http://arstechnica.com/feature-series/specialized-databases/ bibliography