The labelled property graph model is somewhat akin to an object model or an entity relationship diagram. The property graph contains connected entities (aka nodes) which can hold any number of attributes (key-value-pairs). Nodes can be tagged with labels representing their different roles in the domain. In addition to contextualizing node and relationship properties, labels may also serve to attach metadata—index or constraint information—to certain nodes.
In a connected & IoT world, where networks of all types become increasingly preeminent, such a network capability is becoming essential to data analysis. However, like the RDBMS, the graph database is another tool that can be harnessed for good or nefarious means. Thus, it is timely to consider the large-scale security implications of this new technology. dsp have expertise in identifying security vulnerabilities within the Graph Discovery, Graph Prediction and Knowledge Management elements of the graph architecture.
Performance, cybersecurity, and availability measures are best accommodated in system design, because retrofits can be costly. New technologies and applications, however, bring new security and privacy challenges. Furthermore, the consequences of new technology adaptation are often difficult to anticipate. dsp will work with you using their expertise and thorough understanding of the issues to eliminate the costs associated with poorly designed or organically grown deployments.
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