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A step away from
     RDBMS


 Dimitri Krassovski, a.k.a. labria.
RDMBS

• MySQL
• MSSQL Server
• Oracle
• PostgreSQL
• A lot more…
RDMBS


• Tables
• Columns
A Step Away

• Key-value store
• Document database
• Object database
Key-value store

• Memcached
• Redis
• Tokyo Cabinet
• Project Voldemort
Key-value store

• Store and retrieve data by a unique key
• Usually really fast
• Persistent/Non-persistent
Redis:
     KVS with a twist
• Lists: Push, Pop, Range, Trim etc.
• Sets: Add, Remove, Intersect, Union etc.
• Increment/D...
Document DBs

• CouchDB
• MongoDB
• Amazon SimpleDB
• ThruDB
CouchDB
• RESTful JSON interface
• Stores JSON encoded documents
• Document revisions
• Views as documents (Lotus Notes,
 ...
• Documents and even embedded
  documents
• Multiple data types
• Document collections
• Dynamic queries
• Index support
What about Rails?

• MongoMapper
• ActiveCouch
• Redis-store (Session and Cache)
• Waiting for Rails 3
And it FAILS
   (for me, of course)

• CouchDB: slow. And CPU hugry, too!
• MongoDB: simply died on 10M records!
This has nothing to do
with the presentation.

• Use a real queue when you need one
• Use Sphinx as an external index
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A step away from RDBMS

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Transcript of "A step away from RDBMS"

  1. 1. A step away from RDBMS Dimitri Krassovski, a.k.a. labria.
  2. 2. RDMBS • MySQL • MSSQL Server • Oracle • PostgreSQL • A lot more…
  3. 3. RDMBS • Tables • Columns
  4. 4. A Step Away • Key-value store • Document database • Object database
  5. 5. Key-value store • Memcached • Redis • Tokyo Cabinet • Project Voldemort
  6. 6. Key-value store • Store and retrieve data by a unique key • Usually really fast • Persistent/Non-persistent
  7. 7. Redis: KVS with a twist • Lists: Push, Pop, Range, Trim etc. • Sets: Add, Remove, Intersect, Union etc. • Increment/Decrement • Async persistence
  8. 8. Document DBs • CouchDB • MongoDB • Amazon SimpleDB • ThruDB
  9. 9. CouchDB • RESTful JSON interface • Stores JSON encoded documents • Document revisions • Views as documents (Lotus Notes, anyone?) • Map/Reduce
  10. 10. • Documents and even embedded documents • Multiple data types • Document collections • Dynamic queries • Index support
  11. 11. What about Rails? • MongoMapper • ActiveCouch • Redis-store (Session and Cache) • Waiting for Rails 3
  12. 12. And it FAILS (for me, of course) • CouchDB: slow. And CPU hugry, too! • MongoDB: simply died on 10M records!
  13. 13. This has nothing to do with the presentation. • Use a real queue when you need one • Use Sphinx as an external index

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