The buzz around graph databases has been on the rise since 2018, when Amazon Web Services unveiled its Neptune database, signaling its mainstream potential to the business world. Many useful things can be done with graphs. These include clustering objects with similar characteristics, neatly partitioning datasets, plotting paths between related data points, and analyzing the strength of a data point's connections to the rest of its network.
Graph databases are also an ideal architectural solution for analytics and Artificial Intelligence use cases that process vast amounts of data. The databases can also be used as foundations for building fraud detection algorithms, IT operations monitoring systems, social media analysis tools, identity access management systems, and more.
As with any new technology, business leaders must establish a clear business need before rushing to invest in graph databases. Companies at the start of their data journeys may find that relational databases and NoSQL environments serve them perfectly well.
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