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Michaelmalak (talk | contribs) →Lack of novelty: Non-parallel map/reduce in Common Lisp in 1984 |
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DeWitt and Stonebraker have subsequently published a detailed benchmark study in 2009 comparing performance of [[Hadoop|Hadoop's]] MapReduce and [[RDBMS]] approaches on several specific problems.<ref name="sigmod">{{cite web| url=http://database.cs.brown.edu/projects/mapreduce-vs-dbms| title=A Comparison of Approaches to Large-Scale Data Analysis|first1=Andrew |last1=Pavlo |first2=Erik |last2=Paulson |first3=Alexander |last3=Rasin |first4=Daniel J. |last4=Abadi |first5=Deavid J. |last5=DeWitt |first6=Samuel |last6=Madden |first7=Michael |last7=Stonebraker| publisher=Brown University| access-date=2010-01-11}}</ref> They concluded that relational databases offer real advantages for many kinds of data use, especially on complex processing or where the data is used across an enterprise, but that MapReduce may be easier for users to adopt for simple or one-time processing tasks.
The MapReduce programming paradigm was also described in [[Danny Hillis]]'s 1985 thesis <ref name="WDHmit86">{{cite book |author-first=W. Danny |author-last=Hillis |date=1986 |title=The Connection Machine |publisher=[[MIT Press]] |isbn=0262081571 |url-access=registration |url=https://archive.org/details/connectionmachin00hill }}</ref>
In 2010 Google was granted what is described as a patent on MapReduce. The patent, filed in 2004, may cover use of MapReduce by open source software such as [[Hadoop]], [[CouchDB]], and others. In ''[[Ars Technica]]'', an editor acknowledged Google's role in popularizing the MapReduce concept, but questioned whether the patent was valid or novel.<ref>{{cite news |last1=Paul |first1=Ryan |title=Google's MapReduce patent: what does it mean for Hadoop? |url=https://arstechnica.com/information-technology/2010/01/googles-mapreduce-patent-what-does-it-mean-for-hadoop/ |access-date=21 March 2021 |work=Ars Technica |date=20 January 2010 |language=en-us}}</ref><ref name="patent">{{cite web|url=http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=/netahtml/PTO/srchnum.htm&r=1&f=G&l=50&s1=7,650,331.PN.&OS=PN/7,650,331&RS=PN/7,650,331|title=United States Patent: 7650331 - System and method for efficient large-scale data processing|website=uspto.gov}}</ref> In 2013, as part of its "Open Patent Non-Assertion (OPN) Pledge", Google pledged to only use the patent defensively.<ref>{{cite news |last1=Nazer |first1=Daniel |title=Google Makes Open Patent Non-assertion Pledge and Proposes New Licensing Models |url=https://www.eff.org/deeplinks/2013/03/google-makes-open-patent-non-assertion-pledge |access-date=21 March 2021 |work=Electronic Frontier Foundation |date=28 March 2013 |language=en}}</ref><ref>{{cite news |last1=King |first1=Rachel |title=Google expands open patent pledge to 79 more about data center management |url=https://www.zdnet.com/article/google-expands-open-patent-pledge-to-79-more-about-data-center-management/ |access-date=21 March 2021 |work=ZDNet |date=2013 |language=en}}</ref> The patent is expected to expire on 23 December 2026.<ref>{{cite web |title=System and method for efficient large-scale data processing |url=https://patents.google.com/patent/US7650331B1/en |publisher=Google Patents Search |access-date=21 March 2021 |language=en |date=18 June 2004}}</ref>
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