Reporter: Haiping Wang WAMDM Cloud Group Mail:[email protected].
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Transcript of Reporter: Haiping Wang WAMDM Cloud Group Mail:[email protected].
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Outline Why NoSQL?
Four trendsHistory
What is NoSQL?Definition Three fundamental theories
NoSQL categories RDBMS vs. NoSQL
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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
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Trend2:Information connectivity
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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”)
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RDBMS performance
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Trend4:architecture changes
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NoSQL history The term NoSQL was first used in 1998Reintroduced in early 2009 by Eric EvansHot in 2009
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Outline Why NoSQL?
Four trendsHistory
What is NoSQL?Definition Three fundamental theories
NoSQL categories RDBMS vs. NoSQL
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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
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Fundamental theories CAPBASE
APEventual consistency
Causal consistencyRead-your-writes consistencySession consistencyMonotonic read consistencyMonotonic write consistency
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Outline Why NoSQL?
Four trendsHistory
What is NoSQL?Definition Three fundamental theories
NoSQL categories RDBMS vs. NoSQL
![Page 13: Reporter: Haiping Wang WAMDM Cloud Group Mail:lulang1022@yahoo.com.cn.](https://reader035.fdocuments.us/reader035/viewer/2022081503/56649d2e5503460f94a05257/html5/thumbnails/13.jpg)
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
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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
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Key-value stores
Key Value
... name_€#_Stellamood_€#_Happ
ybirthdate%/// 135465645)
…
dog_12
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Bigtable clones
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Document databases
Key document
dog_12
{type: “Dog”,
name: “Stella”, mood: “Happy”, birthdate: 2007-
04-01}
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Graph databases
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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
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Thank you!!!