Data! Data! Data!

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

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 ,
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
22. $30B AGR 6% Relational Databases $5B AGR 35% NoSQL Databases DBMS TAM
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