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MongoDB
                 The fast (don’t think about this like an
                 RDBMS) database alternative.
Wednesday, August 24, 2011
THE ROAD TO MONGODB
   PROJECT




                 RDBMS + ORM
                 BUSINESS LOGIC   DOMAIN MODEL
Wednesday, August 24, 2011
Object Database

                  Attempted to accommodate the OO languages
                  they were meant to support

                        Inheritance, associations, etc.

                  THEY FAILED

                        Too slow, too complicated, doomed!




Wednesday, August 24, 2011
The Google Problem
                  Relational databases are slow and don’t scale well

                        Distribution

                        Replication

                        ACID compliance

                        Vendor lock in

                  Atypical domain model didn’t require ACID
                  transactions

Wednesday, August 24, 2011
The Google Solution
                  Big Table

                        http://labs.google.com/papers/bigtable.html

                             email the authors, they’re great!

                        Petabytes of data across thousands of
                        commodity servers

                        Data separate from logic



Wednesday, August 24, 2011
JSON & BSON
                  Clear, concise and very AJAX friendly

                  Flexible and nestable (you can nest documents)

                  Ubiquitous language support




Wednesday, August 24, 2011
JSON & BSON cont.

                  BSON <> JSON translation can be awkward when
                  dealing with language specific data types

                        Dates, _id fields, etc.

                  Well suited to text/numeric data, not much else




Wednesday, August 24, 2011
Common pitfalls

                  How to create a view or join

                  Enforce data integrity

                  Define data structure

                        Document vs. Table(s)




Wednesday, August 24, 2011
Normalization
                  RDBMS Normalization is intended to...

                        Reduce complexity

                        Discourage duplication of code/data

                        Provide logical mappings for domain elements

                  In mongodb, the document tells the whole story,
                  including a definition of the data



Wednesday, August 24, 2011
Maturity Issues

                  No log file rolling mechanism

                  Awkward tools and querying

                        Accustomed to tabular data (try .pretty())

                        Very little (if any) feedback regarding outcome of
                        commands




Wednesday, August 24, 2011
Queues
                  Many steps, each in it’s
                  own collection

                  Keep high volume
                  collections small & fast

                  Maintain large amounts
                  of statistical data in
                  low volume collections



Wednesday, August 24, 2011
Ready for Business?
                  Business logic must
                  exist in code (including
                  querying data)

                  Transaction boundaries
                  and concurrency must
                  exist in code

                  Speed and reliability
                  are a go (so far :)


Wednesday, August 24, 2011
Questions?



Wednesday, August 24, 2011

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Mongodb

  • 1. MongoDB The fast (don’t think about this like an RDBMS) database alternative. Wednesday, August 24, 2011
  • 2. THE ROAD TO MONGODB PROJECT RDBMS + ORM BUSINESS LOGIC DOMAIN MODEL Wednesday, August 24, 2011
  • 3. Object Database Attempted to accommodate the OO languages they were meant to support Inheritance, associations, etc. THEY FAILED Too slow, too complicated, doomed! Wednesday, August 24, 2011
  • 4. The Google Problem Relational databases are slow and don’t scale well Distribution Replication ACID compliance Vendor lock in Atypical domain model didn’t require ACID transactions Wednesday, August 24, 2011
  • 5. The Google Solution Big Table http://labs.google.com/papers/bigtable.html email the authors, they’re great! Petabytes of data across thousands of commodity servers Data separate from logic Wednesday, August 24, 2011
  • 6. JSON & BSON Clear, concise and very AJAX friendly Flexible and nestable (you can nest documents) Ubiquitous language support Wednesday, August 24, 2011
  • 7. JSON & BSON cont. BSON <> JSON translation can be awkward when dealing with language specific data types Dates, _id fields, etc. Well suited to text/numeric data, not much else Wednesday, August 24, 2011
  • 8. Common pitfalls How to create a view or join Enforce data integrity Define data structure Document vs. Table(s) Wednesday, August 24, 2011
  • 9. Normalization RDBMS Normalization is intended to... Reduce complexity Discourage duplication of code/data Provide logical mappings for domain elements In mongodb, the document tells the whole story, including a definition of the data Wednesday, August 24, 2011
  • 10. Maturity Issues No log file rolling mechanism Awkward tools and querying Accustomed to tabular data (try .pretty()) Very little (if any) feedback regarding outcome of commands Wednesday, August 24, 2011
  • 11. Queues Many steps, each in it’s own collection Keep high volume collections small & fast Maintain large amounts of statistical data in low volume collections Wednesday, August 24, 2011
  • 12. Ready for Business? Business logic must exist in code (including querying data) Transaction boundaries and concurrency must exist in code Speed and reliability are a go (so far :) Wednesday, August 24, 2011