NoSQL Overview

Reporter: Haiping WangWAMDM Cloud Group

Mail:lulang1022@yahoo.com.cn

Outline Why NoSQL?

Four trendsHistory

What is NoSQL?Definition Three fundamental theories

NoSQL categories RDBMS vs. NoSQL

Trend1:data set sizeRapid Increase of Data

57% every year (IDC2007) Double every 1.5 years988EB (1EB=1024PB) data will be produced in

2010 (IDC) 18 million times of all info in books

Trend2:Information connectivity

Trend3:Semi-structure Individualization of content!

In the salary lists of the 1970s, all elements had exactly one job

In the salary lists of the 2000s, we need 5 job columns! Or 8? Or 15?

Trend accelerated by the decentralization of content generation that is the hallmark of the age of participation (“web 2.0”)

RDBMS performance

Trend4:architecture changes

NoSQL history The term NoSQL was first used in 1998Reintroduced in early 2009 by Eric EvansHot in 2009

Outline Why NoSQL?

Four trendsHistory

What is NoSQL?Definition Three fundamental theories

NoSQL categories RDBMS vs. NoSQL

Definition From http://nosql-database.org/

Original intention modern web-scale databases

Characteristics non-relational, Distributed  open-source horizontal scalable schema-free easy replication support simple API eventually consistent / BASE

(not ACID) Others…

From Wikipedialoosely defined class of

non-relational data storesnot require fixed table

schemasAvoid join operationsScale horizontally

NoSQL is NOT Only SQL

Fundamental theories CAPBASE

APEventual consistency

Causal consistencyRead-your-writes consistencySession consistencyMonotonic read consistencyMonotonic write consistency

Outline Why NoSQL?

Four trendsHistory

What is NoSQL?Definition Three fundamental theories

NoSQL categories RDBMS vs. NoSQL

NoSQL categories Key-value stores

Based on DHTs / Amazon's Dynamo paper Data model: (global) collection of K-V pairs Example: Dynomite, Voldemort, Tokyo

BigTable clones Based on Google's BigTable paper Data model: big table, column families Example: Hbase, Hypertable

NoSQL categories Document databases

Inspired by Lotus Notes Data model: collections of K-V collectionsExample: CouchDB, MongoDB

Graph databasesInspired by Euler & graph theory Data model: nodes, rels, K-V on both Example: AllegroGraph, VertexDB, Neo4j

Key-value stores

Key Value

... name_€#_Stellamood_€#_Happ

ybirthdate%/// 135465645)

…

dog_12

Bigtable clones

Document databases

Key document

dog_12

{type: “Dog”,

name: “Stella”, mood: “Happy”, birthdate: 2007-

04-01}

Graph databases

RDBMS vs. NoSQLStrong consistency vs. Eventual consistency Big dataset vs. HUGE datasets Scaling is possible vs. Scaling is easySQL vs. Map-ReduceGood availability vs. Very high availability

Thank you!!!