Applying Graph Analytics to Game of Thrones
by Amy Hodler & Mark Needham, Neo4j (guest author), 12 June 2019
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In this post, we review how organizations are integrating graph transactions and analytic processing and then dive deeper into graph algorithms. We’ll provide examples of using graph algorithms on Game of Thrones data to illustrate how to get started. Note that portions of this content have been taken from our O’Reilly book, Graph Algorithms: Practical Examples in Apache Spark & Neo4j, which you can download for free.
» moreGQL - initiating an industry standard property graph query language
by Alastair Green (guest author), 30 May 2018
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GQL stands for “Graph Query Language”. GQL doesn’t exist yet: it’s a proposal to create a standard declarative language - designed to live alongside and fit well with SQL - that is specifically designed for the property graph data model.
» moreEmerging and fading trends in database management systems
by Paul Andlinger, 4 October 2016
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Articles on database technologies are jammed with buzzwords and prophecies of new trends, just like any other technology. We use the collected data of our DB-Engines Ranking to have a look at some of these trends.
» moreEnriching Property Graphs with Relationship Objects
by Jans Aasman (guest author), 21 June 2016
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In many graph database applications we find that a link between two nodes is quite complex. Conventional property graph databases try to manage the complexity by putting properties on the edges between nodes, but this technique has significant limitations. To overcome the limitations, this article introduces the relationship objects pattern.
» moreThe openCypher Project: Help Shape the SQL for Graphs
by Emil Eifrem (guest author), 22 December 2015
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Learn how you can get involved with the graph database community’s newest collaboration: the openCypher project, an open source query language for graphs.
» moreMaster Data Management Remains Siloed Without Semantics
by Jans Aasman (guest author), 16 November 2015
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As Big Data continues to grow, companies are increasing their commitments to extract every last drop of value from the information they gather. Since siloed data has limited value, organizations are also embracing a more comprehensive strategy of managing data across multiple data domains. But this requires a shift away from traditional Master Data Management (MDM) to broader and more flexible data governance environments that enable enterprises to quickly synthesize diverse data sources that can result in transformative business decisions.
» moreGraph DBMS increased their popularity by 500% within the last 2 years
by Paul Andlinger, 3 March 2015
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Graph DBMS show an extraordinary momentum and are making their way into enterprises.
» moreCassandra gained one rank and improves to 9th position
by Paul Andlinger, 2 April 2014
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While Cassandra achieves its best position ever, other trends are stabilizing in this months ranking.
» moreGraph DBMSs are gaining in popularity faster than any other database category
by Matthias Gelbmann, 21 January 2014
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When we look at how much various categories of database management systems increased their popularity last year, Graph DBMSs are the clear winner with more than 250% increase.
» moreOur DB-Engines ranking identifies the most popular DBMS systems in various database model categories
by Paul Andlinger, Matthias Gelbmann, 22 January 2013
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We have introduced sub-rankings by spliting up the DBMS systems per database models.
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