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Why NoSQL Makes Sense
Why NoSQL Makes Sense

        NoSQL Now
  Dwight Merriman / 10gen
  Dwight Merriman / 10gen
signs we needed something different
    signs we needed something different

•   doubleclick ‐ 400,000 ads/second
•   people writing their own stores
    people writing their own stores
•   caching is de rigueur
•   complex ORM frameworks
•   computer architecture trends
        p
•   cloud computing
the db space 2000 
                the db space 2000 ‐ 2010
                                                        + great for complex 
    dh          i
+ ad hoc queries easy                                   transactions
+ SQL gives us a standard                               + great for tabular data
protocol for the interface                              + ad hoc queries easy
between clients and                                     ‐ O<‐>R mapping hard
servers                                                 ‐ speed/scale challenges
+ scales horizontally                                   ‐ not super agile
better than operational 
dbs. some scale limits at        BI /       OLTP / 
massive scale
      i      l                reporting
                                     i    operational
                                                i   l
‐ schemas are rigid
‐ real time is hard; very 
good at bulk nightly data 
loads
the db space 2000 
                the db space 2000 ‐ 2010
                                                        + great for complex 
    dh          i
+ ad hoc queries easy                                   transactions
+ SQL gives us a standard                               + great for tabular data
protocol for the interface                              + ad hoc queries easy
between clients and                                     ‐ O<‐>R mapping hard
servers                                                 ‐ speed/scale challenges
+ scales horizontally                                   ‐ not super agile
better than operational 
dbs. some scale limits at        BI /       OLTP / 
massive scale
      i      l                reporting
                                     i    operational
                                                i   l
‐ schemas are rigid
‐ real time is hard; very 
good at bulk nightly data 
loads




               less issues 
                  here
the db space 2000 
                the db space 2000 ‐ 2010
                                                                         + great for complex 
    dh          i
+ ad hoc queries easy                                                    transactions
+ SQL gives us a standard                                                + great for tabular data
protocol for the interface                                               + ad hoc queries easy
between clients and                                                      ‐ O<‐>R mapping hard
servers                                                                  ‐ speed/scale challenges
+ scales horizontally                                                    ‐ not super agile
better than operational 
dbs. some scale limits at            BI /       OLTP / 
massive scale
      i      l                    reporting
                                         i    operational
                                                    i   l
‐ schemas are rigid                                                      caching
‐ real time is hard; very 
good at bulk nightly data 
loads

                                                                                    app layer 
                                                            flat files             partitioning
                              map/reduce
the db space
 the db space
                                   + fits OO programming 
                                   wellll
                                   + agile
                                   + speed/scale
                                   ‐ querying a little less 
                      scalable 
                         l bl      add hoc
                                     dd h
                   nonrelational   ‐ not super transactional
BI / reporting       (“nosql”)     ‐ not sql




            OLTP / 
            OLTP /
          operational
data models
as simple as possible 
   but no simpler
   b           l
as simple as possible 
              but no simpler
              b           l
• need a good degree of functionality to handle 
  a large set of use cases
  – sometimes need strong consistency / atomicity
  – secondary indexes
  – ad hoc queries
as simple as possible 
               but no simpler
               b           l
• but, leave out a few things so we can scale
  – no choice but to leave out relational
  – distributed transactions are hard to scale
as simple as possible 
              but no simpler
              b           l
• to scale, need a new data model.  some 
  options:
  – key/value
  – columnar / tabular
  – document oriented (JSON inspired)
• opportunity to innovate ‐> agility
   pp       y                 g y
mongodb philosphy
                  mongodb philosphy
•   No longer one‐size‐fits all.  but not 12 tools either.
    N l              i fit ll b t t 12 t l ith
•   By reducing transactional semantics the db provides, one can still solve an 
    interesting set of problems where performance is very important, and 
    horizontal scaling then becomes easier.
    hori ontal scaling then becomes easier
•   Non‐relational (no joins) makes scaling horizontally practical
•   Document data models are good
•   Keep functionality when we can (key/value stores are great, but we nee 
    more)
•   Database technology should run anywhere, being available both for 
    running on your own servers or VMs, and also as a cloud pay‐for‐what‐
    you‐use service.  And ideally open source...
Questions?

         http://blog.mongodb.org/
                @mongodb
                me 
                me ‐ @dmerr

                www.mongodb.org
http://groups.google.com/group/mongodb‐user
htt //                l    /     /     db
        irc://irc.freenode.net/#mongodb



                  thanks

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Why NoSQL Makes Sense

  • 1. Why NoSQL Makes Sense Why NoSQL Makes Sense NoSQL Now Dwight Merriman / 10gen Dwight Merriman / 10gen
  • 2. signs we needed something different signs we needed something different • doubleclick ‐ 400,000 ads/second • people writing their own stores people writing their own stores • caching is de rigueur • complex ORM frameworks • computer architecture trends p • cloud computing
  • 3. the db space 2000  the db space 2000 ‐ 2010 + great for complex  dh i + ad hoc queries easy transactions + SQL gives us a standard  + great for tabular data protocol for the interface  + ad hoc queries easy between clients and  ‐ O<‐>R mapping hard servers ‐ speed/scale challenges + scales horizontally  ‐ not super agile better than operational  dbs. some scale limits at  BI /  OLTP /  massive scale i l reporting i operational i l ‐ schemas are rigid ‐ real time is hard; very  good at bulk nightly data  loads
  • 4. the db space 2000  the db space 2000 ‐ 2010 + great for complex  dh i + ad hoc queries easy transactions + SQL gives us a standard  + great for tabular data protocol for the interface  + ad hoc queries easy between clients and  ‐ O<‐>R mapping hard servers ‐ speed/scale challenges + scales horizontally  ‐ not super agile better than operational  dbs. some scale limits at  BI /  OLTP /  massive scale i l reporting i operational i l ‐ schemas are rigid ‐ real time is hard; very  good at bulk nightly data  loads less issues  here
  • 5. the db space 2000  the db space 2000 ‐ 2010 + great for complex  dh i + ad hoc queries easy transactions + SQL gives us a standard  + great for tabular data protocol for the interface  + ad hoc queries easy between clients and  ‐ O<‐>R mapping hard servers ‐ speed/scale challenges + scales horizontally  ‐ not super agile better than operational  dbs. some scale limits at  BI /  OLTP /  massive scale i l reporting i operational i l ‐ schemas are rigid caching ‐ real time is hard; very  good at bulk nightly data  loads app layer  flat files partitioning map/reduce
  • 6. the db space the db space + fits OO programming  wellll + agile + speed/scale ‐ querying a little less  scalable  l bl add hoc dd h nonrelational ‐ not super transactional BI / reporting (“nosql”) ‐ not sql OLTP /  OLTP / operational
  • 8. as simple as possible  but no simpler b l
  • 9. as simple as possible  but no simpler b l • need a good degree of functionality to handle  a large set of use cases – sometimes need strong consistency / atomicity – secondary indexes – ad hoc queries
  • 10. as simple as possible  but no simpler b l • but, leave out a few things so we can scale – no choice but to leave out relational – distributed transactions are hard to scale
  • 11. as simple as possible  but no simpler b l • to scale, need a new data model.  some  options: – key/value – columnar / tabular – document oriented (JSON inspired) • opportunity to innovate ‐> agility pp y g y
  • 12. mongodb philosphy mongodb philosphy • No longer one‐size‐fits all.  but not 12 tools either. N l i fit ll b t t 12 t l ith • By reducing transactional semantics the db provides, one can still solve an  interesting set of problems where performance is very important, and  horizontal scaling then becomes easier. hori ontal scaling then becomes easier • Non‐relational (no joins) makes scaling horizontally practical • Document data models are good • Keep functionality when we can (key/value stores are great, but we nee  more) • Database technology should run anywhere, being available both for  running on your own servers or VMs, and also as a cloud pay‐for‐what‐ you‐use service.  And ideally open source...
  • 13. Questions? http://blog.mongodb.org/ @mongodb me  me ‐ @dmerr www.mongodb.org http://groups.google.com/group/mongodb‐user htt // l / / db irc://irc.freenode.net/#mongodb thanks