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How I learned to stop worrying and love Oracle

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Keynote presentation at the AUSOUG 20/20 conference series, Perth/Melbourne November 2009

Keynote presentation at the AUSOUG 20/20 conference series, Perth/Melbourne November 2009

Published in Technology , Business
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  • Apologies, I’m a database type.....Quest is best known for toad, but we also have enterprise monitoring across all levels of the stackIn Melbourne, SQL Navigator + the spotlights. It’s not a complete co-incidence about the star trek theme.
  • I’m worried about the Toad in the red shirt – we all know that red-shirt crewmen die in Star Trek!
  • I know what you’re thinking ... Why the big glassesI wondered to, until I found this picture... I was subliminally role-modeling on BillLarry, of course, doesn’t have the same geeky look.... Or does he. Recently discovered high school photo’s suggest he may have been a big-glassed nerd as well.So we might call 1987 the year of the big glassed geek
  • In 1987 I was working for the Australian Govt. We were moving from centralized mainframe in canberra to minicomputers in each state office (VAX VMS and oracle)
  • That’s a predictable linear growth curve. Gets much worse for unpredictable or cyclic demand So I think it’s real, and it excites me because it represents the realization of a more industrialized model for providing computing resources. In the early days of electricity everybody had thier own power sources and every company needed engineers as a result. Nowdays, few companies need that...
  • Data warehouses doubling every three years.
  • Mention columnar compression Mention flash cache in the database In memory ParalelismMPP styles similar to whats happening in M-R
  • So while I worry about the red-shirt TOAD, I’m not really worried about Oracle. Oracle remains a highly technically innovative company as well as a skilled in the business of software. I’ve certainly got no regrets specializing in Oracle technology all those years ago. Quest is a fairly diversified company and has no vested interest in Oracle per see. We aim to be a strategic partner across all of your technologies: Oracle, Microsoft, Vmware and in emerging technologies.

Transcript

  • 1. How I learned to stop worrying and love Oracle
    Guy Harrison
    Director Research and Development, Melbourne
    guy.harrison@quest.com
    www.guyharrison.net
  • 2. Introductions
  • 3. http://www.motivatedphotos.com/?id=17760
  • 4.
  • 5. Looking back to 1987…..
    http://www.yearbookyourself.com/
  • 6. 1987: RDBMS/Minicomputer revolution
    IBM-based MVS mainframes giving way to Minicomputer architectures
    Era of Big glasses
    32-bit computers such as DEC VAX
    Still dumb terminals
    Oracle vs IMS/Adabas/DB2
  • 7. 1992: Client server revolution
    IBM PC allows for off loading of some processing to the client
    Richer Character mode interfaces
    First graphical interfaces: Windows 3.0
    Oracle vs Sybase/Ingres/dBase III
  • 8. 1999: Internet/Y2K gold rush
    Massive IT budgets
    Scalability at all costs
    Java
    3-tier applications
    Oracle unchallenged
  • 9. 2005: After the gold rush
    • TCO and ROI
    • 10. Cost not capability
    • 11. SQL Server gains share
    • 12. Oracle responds with XE (low end), automation (TCO) and RAC (high end)
  • 2009: Big Data and Clouds
    Volumes of data strain commercial RDBMS
    Cloud computing mania
  • 13. Why worry?
    Dominant players often fail quickly
    Being on the wrong side of a paradigm shift hurts
    Theory of disruptive innovation helps explain rapid shifts
  • 14. Functionality demanded at high end of market
    Functionality
    Sustaining
    Innovation
    Functionality demanded at low end of market
    Disruptive
    Innovation
    Time
    Disruptive Innovation
    Oracle RAC
    Oracle10g
    Oracle9i
    OracleXE
    The Innovators Dilemma, Clayton Christensen, Harvard University Press
  • 15. Larry, Richard and the cloud
    the provision of virtualized application software, platforms or infrastructure across the network, in particular the internet.
    Larry Ellison (Sep 08):
    “we’ve redefined cloud computing to include everything that we already do … It’s complete gibberish. It’s insane. When is this idiocy going to stop?:
    Richard Stallman (Oct 08):
    "It's worse than stupidity: it's a marketing hype campaign."
    Larry Ellison (Sep 09):
    “It’s this nonsense ... Water vapour”
  • 16. Cloud Ingredients and recipes
    Utility
    Computing
    AKA
    Private
    Cloud
    Clustering
    Single workload
    across
    multiple host
    SaaS
    Software as a Service
    Salesforce.com
    Gmail
    Internet
    Cloud
    Computing
    Virtualization
    Multiple workloads
    on
    Single host
    IaaS
    Infrastructure as a Service
    Amazon Web Services
    Joyent
    Grid management
    Allocate resources on
    demand
    PaaS
    Platform as a Service
    Google App Engine
    Azure
  • 17. Elastic provisioning
    Capacity / Demand
    Demand
    Hardware upgrade
    Under provisioned
    Capacity
    Over provisioned
    Time
  • 18. Big Data
    The Industrial Revolution of data*
    User generated data:
    Twitter, Facebook, Amazon
    Machine generated data:
    RFID, POS, cell phones, GPS
    Traditional RDBMS neither economic or capable
    * http://radar.oreilly.com/2008/11/the-commoditization-of-massive.html
  • 19. Big data 1: Google
  • 20. Map Reduce
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Start
    Reduce
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
    Map
  • 21. Hadoop: Open source Map-reduce
    Yahoo! Hadoop cluster:
    4000 nodes
    16PB disk
    64 TB of RAM
    32,000 Cores
  • 22. Big Data 2: Twitter (and Web 2.0)
  • 23. The fail whale
  • 24. Twitter 2009
  • 25. Memcached and Sharding
    Web Servers
    Memcached servers
    Database Servers
    Master
    Slave
    Slave
  • 26. The NoSQL movement
  • 27. CAP Theorem: You can’t have it all
    Eventual consistency:
    “when no updates occur for a long period of time, eventually all updates will propagate through the system and all the replicas will be consistent.”
    Availability (Total redundancy)
    Consistency: ACID transactions
    RAC
    No GO
    NoSQL DB
    Partition Tolerance: Infinite scaleout
  • 28. Non-Relational DBs
    Column oriented:
    BigTable
    HyperTable
    Hbase
    SimpleDb
    Azure Table Services
    Cassandra
  • 39. Big Data 3: Data Warehousing
  • 40. Data warehousing and Oracle
  • 41. DATAllegro architecture
  • 42. Column Databases (Vertica)
    Data is stored together in columns
    Very fast answers to analytic aggregate queries
    Better compression
    Not write optimized
  • 43. Oracle EXADATA
    RAC clusters provide MPP
    Dedicated storage servers
    High Speed infiniband channels
    Smart storage reduces data transfer requirements
  • 44. Big Data vs. Fast Data
  • 45. Economics of SSD
  • 46. Hierarchical storage management
    $/GB
    $/IOP
  • 47. Oracle 2009 innovations
    Sun Oracle database machine
    Exadata flash cache
    Database flash cache (coming soon)
    Hybrid Columnar compression
  • 48. Not worrying, just wondering...
    How will Oracle deal respond to Hadoop?
    Will Oracle play in the NoSQL database world?
    What will happen to MySQL?
    What will happen to red-shirt TOAD?