Graph databases explained

The strength of a database can be measured using four principal factors: Integrity, performance, efficiency and scalability. The data query ought to become quicker and simpler – the main purpose of graph databases can be roughly summarized in this way. Where relational databases reach their capacity limits, the graph-based model is particularly agile, because complexity and the quantity of data don’t negatively influence the query process in this model.

Also, with the graph database model, real facts can be stored in a natural way. The structure used is very similar to human thinking, and this is why the links are so clear. Graph databases are not a complete solution, though. They are limited, for example, where scalability is concerned. As they are principally designed for one-tier architecture, growth represents a (mathematical) challenge. Plus, there is still no uniform query language.

An overview of the advantages and disadvantages of graph databases:

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