NoSQL

South London Geek Night14/07/2010

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

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