Data Antipatterns

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Are you running a database in the cloud? Worried that you're doing it wrong?

Engine Yard supports a broad set of databases with flexibility for customers to modify and configure. However, freedom to adapt and extend standard functionality comes with unexpected negative consequences: modifications can seriously affect durability and performance. I've observed common problems, patterns and best practices with big (and not so big) data. I'll highlight the most common pitfalls and discuss how to avoid them.

Video for this talk is available here: http://vimeo.com/83755776

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Data Antipatterns

  1. 1. DATA ANTI PATTERNS
  2. 2. I work with Databases And I’m a happy dog! I S N O M E B S R A ines @ Engine Yard.com @Randommood
  3. 3. Engine Yard
  4. 4. ZOMG, the horror!
  5. 5. .BACKUPS yes, we are going there
  6. 6. “I know you. You know you. And I know you know that I know you” White Goodman (no relationship to White October)
  7. 7. Boring Definition #1 Copy and archiving of data Goal is to restore the state of a DB Backups Many types - blah
  8. 8. Anti-Pattern #1 Not free, they requires resources Full backup every hour, really? Taking too What about backup many backups retention?
  9. 9. Anti-Pattern #2 Taking too few backups Enough to minimize the risk of data loss due to corrupted backup files yes,

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