Graph Databases: Their Power and Limitations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10297454" target="_blank" >RIV/00216208:11320/15:10297454 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-24369-6_5#page-1" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-24369-6_5#page-1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-24369-6_5" target="_blank" >10.1007/978-3-319-24369-6_5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Graph Databases: Their Power and Limitations

Popis výsledku v původním jazyce

Real world data offers a lot of possibilities to be represented as graphs. As a result we obtain undirected or directed graphs, multigraphs and hypergraphs, labelled or weighted graphs and their variants. A development of graph modelling brings also newapproaches, e.g., considering constraints. Processing graphs in a database way can be done in many different ways. Some graphs can be represented as JSON or XML structures and processed by their native database tools. More generally, a graph database isspecified as any storage system that provides index-free adjacency, i.e. an explicit graph structure. Graph database technology contains some technological features inherent to traditional databases, e.g. ACID properties and availability. Use cases of graph databases like Neo4j, OrientDB, InfiniteGraph, FlockDB, AllegroGraph, and others, document that graph databases are becoming a common means for any connected data. In Big Data era, important questions are connected with scalability fo

Název v anglickém jazyce

Graph Databases: Their Power and Limitations

Popis výsledku anglicky

Real world data offers a lot of possibilities to be represented as graphs. As a result we obtain undirected or directed graphs, multigraphs and hypergraphs, labelled or weighted graphs and their variants. A development of graph modelling brings also newapproaches, e.g., considering constraints. Processing graphs in a database way can be done in many different ways. Some graphs can be represented as JSON or XML structures and processed by their native database tools. More generally, a graph database isspecified as any storage system that provides index-free adjacency, i.e. an explicit graph structure. Graph database technology contains some technological features inherent to traditional databases, e.g. ACID properties and availability. Use cases of graph databases like Neo4j, OrientDB, InfiniteGraph, FlockDB, AllegroGraph, and others, document that graph databases are becoming a common means for any connected data. In Big Data era, important questions are connected with scalability fo

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA13-08195S" target="_blank" >GA13-08195S: Vysoce škálovatelné paralelní a distribuované metody zpracování vědeckých dat</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Computer Information Systems and Industrial Management

ISBN

978-3-319-24368-9

ISSN

—

e-ISSN

—

Počet stran výsledku

12

Strana od-do

58-69

Název nakladatele

Springer International Publishing

Místo vydání

Switzerland

Místo konání akce

Warsaw

Datum konání akce

24. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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