Understanding the relationships in graph database theory allows us to work with the new 'shape' of data itself. Businesspeople like graphs. C-suite executives are fond of pie charts, Venn diagrams, ...
Graph databases explicitly express the connections between nodes, and are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. There has ...
Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.
My fans know that my standard test for everything from PaaS (platform as a service) to alternative programming languages is something I call Granny’s Addressbook, a simple CRUD application. As it ...
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Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...
Graph databases represent one of the fastest-growing areas in the database market. MarketsandMarkets’ report on graph databases predicts that graph databases will grow from $1.9 billion in 2021 to ...
A database structure that ties together relationships between data more thoroughly than a relational database (RDBMS). There are fewer restraints, and data elements can be linked in almost any manner.
Every decade seems to have its database. During the 1990s, the relational database became the principal data environment, its ease of use and tabular arrangement making it a natural for the growing ...
Automotive giant Daimler is using Neo4j's graph database technology in its HR department. ZDNet spoke to Jochen Linkohr, the manager of HR IT at Daimler, to find out more. ZDNet: When did you start ...
In this article, I explain why the first app built on a knowledge graph should be an enterprise data catalog. I then clarify why any catalog equipped to grow, scale, and evolve with the modern data ...