NoSQL: what does it mean, how did we get here, and why should I care? - Hugo Rodger-Brown

NoSQL
South London Geek Night
14/07/2010

NoSQL
What does it mean?
RDBMS legacy and rise of NoSQL
NoSQL classification
Pros and Cons
Possible use cases
Real-world examples
What next?

Who am I?
Hugo Rodger-Brown
CTO @ Profero Connect
twitter.com/hugorodgerbrown
hugorodgerbrown.blogspot.com
Things I like: SEO, Scale, Social media
Things I don’t: Databases

What does it mean?
Movement, not a specification
Subjective term (like Web 2.0)
Originally used in 1998
Reintroduced at Rackspace to refer to non-RDBMS
NoSQL != No SQL
NoSQL == Not Only SQL ?

NoSQL Comment

RDBMS Legacy
Efficient data storage
Powerful querying capabilities (SQL)
Support ACID Transactions
Mature, well supported
Ubiquitous
Bottom-up design
Storage is cheap
O/R Impedance
Complex to manage
Always the bottleneck
Who really needs transactions?

Rise of NoSQL
Internet
Google
2006 Bigtable whitepaper (Google)
“a sparse, distributed multi-dimensional sorted map”
2007 Dynamo whitepaper (Amazon)
2008 Cassandra released (Facebook)
“a BigTable data model running on an Amazon Dynamo-like infrastructure”
2009 Voldemort released (LinkedIn)
“a big, distributed, persistent, fault-tolerant hash table”

Rise of NoSQL – Amazon
“There are many services on Amazon’s platform that only need primary-key access to a data store. For many services, such as those that provide best seller lists, shopping carts, customer preferences, session management, sales rank, and product catalog, the common pattern of using a relational database would lead to inefficiencies and limit scale and availability. Dynamo provides a simple primary-key only interface to meet the requirements of these applications.”

NoSQL Data Store Classifications
Key-Value store
Amazon SimpleDB, Amazon Dynamo (Amazon), Tokyo Cabinet, Voldemort (Gilt Groupe)
Wide-column (sparse) store
Hadoop (Yahoo, EBay), Cassandra (Facebook), Bigtable (Google!), Azure Table Storage (MSFT), Excel(!)
Document database
MongoDB, CouchDB (BBC), RavenDB
Graph database
Neo4J, InfoGrid
Object database
Db4o, Versant, Perst, Cache
Data Grids
Infinispan, GigaSpaces, Terracotta

Why NoSQL
Good
Flexible (schema-less)
Very scalable
Simple to use and operate
Eventually consistent
Cheap
Suited to Web applications
Bad
Immature
No common standards
Poor transaction support
Poor query support
New mindset required

NoSQL Use Cases
Good Examples
Logging data
Shopping carts
Favourites
Preferences
Session data
Mock data providers
Temporary / working data
Variable schema data
Stick with RDBMS
Transactions (orders etc.)
LOB applications
Anything involving $$$
Business-critical data
Reporting

Real-world Examples

Real-world Examples
“As I described in an earlier blog post, the new BBC homepage has been built on a whole new technical architecture. Since launching we’ve found an issue with the service we use to save users’ customisation settings. Although we ran a public beta for more than 2 months, this problem only became apparent when we moved the whole audience across to the new site, increasing the load on the platform 20 times. Despite thorough load testing before launch we were unable to accurately predict the type and combination of customisations that users would perform, and as a result we now need to re-architect the way we save your homepage customisation settings in a more efficient way.”

Summary
NoSQL is not a replacement for RDBMS
No two scenarios are the same
Use best tool for the job
Experiment

Demo - CouchDB

NoSQL: what does it mean, how did we get here, and why should I care? - Hugo Rodger-Brown

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NoSQL: what does it mean, how did we get here, and why should I care? - Hugo Rodger-Brown Presentation Transcript