Polyglot Persistence - Two Great Tastes That Taste Great Together

Polyglot Persistence Two Great Tastes That Taste Great Together! John Wood john_p_wood@yahoo.com @johnpwood

About Me ● Software Developer at Interactive Mediums ● Primarily work on a web application that allows our customers to engage and interact with their customers ● Writing code for about 15 years ● Tinkering with NoSQL for about 1.5 years ● Have a NoSQL solution that has been running in production for a year

You Now Have A Choice

The RDBMS Is No Longer The Default Choice

The RDBMS Is No Longer The Default Choice ● Can be very difficult to scale horizontally ● Schemas can be difficult to maintain and migrate ● For some applications, the data integrity features of the RDBMS are an unnecessary overhead ● Data constraints and JOINs can be expensive at runtime

NoSQL Databases Have Stepped Up To Address These Issues

NoSQL Databases Have Stepped Up To Address These Issues ● Schema-less ● Little to no data integrity enforcement ● Self-contained data ● Eventually consistent ● Easy to scale horizontally to add processing power and storage

But The RDBMS Is Far From Dead

But The RDBMS Is Far From Dead ● Incredibly mature, and battle tested ● Immediate and constant consistency ● Integrity of data is enforced ● Efficient use of storage space if data normalized properly ● Supported by everyone and everything (tools, frameworks, libraries, etc) ● Incredibly flexible and powerful query language ● Help is plentiful and easy to find

Choice is good...right?

Decisions, Decisions...

You Don't Have to Choose

“You've got your chocolate in my peanut butter!”

Polyglot Persistence

pol●y●glot - Adjective Knowing or using several languages

pol●y●glot - Adjective Knowing or using several languages per●sist●ence - Noun The continued or prolonged existence of something

Polyglot Persistence The continued or prolonged existence of something using several languages

Polyglot Persistence The continued or prolonged existence of something using several languages databases

“Polyglot Persistence, like polyglot programming, is all about choosing the right persistence option for the task at hand.” - Scott Leberknight, October, 2008 http://www.nearinfinity.com/blogs/scott_leberknight/polyglot_persistence.html

Why On Earth Would You Want To Do This?

CAP Theorem http://en.wikipedia.org/wiki/CAP_theorem

http://blog.nahurst.com/visual-guide-to-nosql-systems

Compromise

Consistency and Data Integrity + Scalability and Flexibility

Support A Wide Range of Storage Requirements

Get The Job Done Faster, With Better Quality

DB Doesn't Just Stand For Database

Don't Swim Upstream

Possible Use Cases

Use A NoSQL Database For A Particular Application Feature

Use A NoSQL Database For Speedy Batch Processing

Use A NoSQL Database For Distributed Logging

Use A NoSQL Database For Large Tables

Use A RDBMS For Reporting

Sounds Great! What's The Catch?

Difficult For Data In Different Databases To Interact

You Now Have To Decide Where To Store Data

Increased Application And Deployment Complexity

Additional Administrative Responsibilities

Training

What Will This Do To My Beautiful Code?

It's All About The Layers

class User < ActiveRecord::Base end class ContestEntry < CouchRest::ExtendedDocument property :entry_number end

class User < ActiveRecord::Base def contest_entries ContestEntry.entries_for_user(self.id) end end class ContestEntry < CouchRest::ExtendedDocument property :entry_number property :user_id def self.entries_for_user(user_id) # Execute your view to fetch the contest entries end def user User.f nd_by_id(user_id) i end end

Additional Options Available

So, Who Is Actually Doing This?

● Primary MySQL database with a backup ● A few very large tables, containing 5M – 30M rows each, and growing quickly ● Increasing query execution time ● Some pages on the web app were timing out ● Increasing database migration time ● Rigid schema of the RDBMS was preventing some planned features from moving forward

● Brought in a consultant to help us optimize our MySQL setup ● Optimized slow queries ● Added some indexes ● Offloaded some work to the backup database ● Considered the use of summary tables for statistics

● Migrated old data from large tables to CouchDB ● Using CouchDB views to aggregate summary data ● Data is imported and views are updated nightly ● Queries for statistics now very fast ● Using Lucene (via couchdb-lucene) for full text searching ● Taking full advantage of CouchDBs schema- less nature in several new application features

It's Not All Rainbows And Unicorns

● CouchDB databases and views can be very large on disk ● Some queries could not be substituted with CouchDB views ● Indexing tens of millions of documents for full text search with Lucene takes weeks ● Development takes longer, as the map/reduce model requires additional thought and planning ● Changing/Upgrading views in production not straightforward http://www.couch.io/migrating-to-couchdb

http://twitter.com/about/opensource

● Vertically and horizontally partitioned MySQL ● Several layers of aggressive caching, all application managed ● Schema changes impossible, resulting in the use of bitfields and piggyback tables ● Hardware intensive ● Error prone ● Hitting MySQL limits ● Already eventually consistent

HBase FlockDB

● Migrating from MySQL to Cassandra as their main online data store ● Hadoop/HBase used for people search feature ● FlockDB used to manage the social graph ● Hadoop for analytics ● “As with all NoSQL systems, strengths in different situations” - Kevin Weil, Analytics Lead, Twitter http://www.slideshare.net/kevinweil/nosql-at-twitter-nosql-eu-2010

● Increased availability ● The ability to support new features ● The ability to analyze their massive amount of data in a reasonable amount of time http://www.slideshare.net/kevinweil/nosql-at-twitter-nosql-eu-2010

Right Tool For The Job

Thanks! john_p_wood@yahoo.com @johnpwood

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Polyglot Persistence - Two Great Tastes That Taste Great Together

by John Wood

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