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NOSQL Overview Lightning Talk (Scalability Geekcruise 2009)
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NOSQL Overview Lightning Talk (Scalability Geekcruise 2009)

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15 min lightning talk introducing the NOSQL space to the Scalability Geekcruise 2009.

15 min lightning talk introducing the NOSQL space to the Scalability Geekcruise 2009.

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    NOSQL Overview Lightning Talk (Scalability Geekcruise 2009) NOSQL Overview Lightning Talk (Scalability Geekcruise 2009) Presentation Transcript

    • NOSQL 15 minutes of write performance #neo4j Emil Eifrem @emileifrem CEO, Neo Technology emil@neotechnology.com
    • Trend 1: data set size 40 2007 Source: IDC 2007
    • 988 Trend 1: data set size 40 2007 2010 Source: IDC 2007
    • Trend 2: connectedness Giant Global Information connectivity Graph (GGG) Ontologies RDF Folksonomies Tagging User- Wikis generated content Blogs RSS Hypertext Text documents web 1.0 web 2.0 “web 3.0” 1990 2000 2010 2020
    • Trend 3: 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”)
    • Aside: RDBMS performance Relational database Salary List Performance Majority of Webapps Social network Semantic } Trading custom Data complexity
    • Trend 4: architecture 1990s: Database as integration hub
    • Trend 4: architecture 2000s: (Slowly towards...) Decoupled services with own backend
    • Why NoSQL 2009? Trend 1: Size. Trend 2: Connectivity. Trend 3: Semi-structure. Trend 4: Architecture.
    • NoSQL overview
    • First off: the damn name NoSQL is NOT “Never SQL” NoSQL is NOT “No To SQL”
    • NOSQL is simply Not Only SQL!
    • Four (emerging) NOSQL categories Key-value stores Based on 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
    • Four (emerging) NOSQL categories Document databases Inspired by Lotus Notes Data model: collections of K-V collections Example: CouchDB, MongoDB Graph databases Inspired by Euler & graph theory Data model: nodes, rels, K-V on both Example: AllegroGraph, VertexDB, Neo4j
    • NOSQL data models Size Key-value stores Bigtable clones Document databases Graph databases Complexity
    • NOSQL data models Size Key-value stores Bigtable clones Document databases Graph databases (This is still billions of 90% nodes & relationships) of use cases Complexity
    • Looking ahead: polyglot persistence SQL && NOSQL
    • http://neotechnology.com