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Graph databases tend to be purpose-built for storing and navigating relationships. They utilize nodes for storing data entities. Additionally, they use edges for storing relationships between entities. The edge always has get an end node, a start node, and direction for describing child-parent relationships, ownership, actions, etc.

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What is Meant by Graph Databases?

A graph database is the method of accessing, storing, and navigating huge interrelated datasets which makes relationships between data pretty essential similar to the data. This also follows that a graph database forms novice forms of relationships between some content strings that turn highly useful for various dynamic effects and personalization all across content sets.


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Another method to see graph databases is similar to a brain which links an entire matrix of concepts into one coherent whole. It provides machines a novice method to have good understanding of concept relationships into more powerful and complete way in place of a relational database.

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Use Cases of Graph Databases

Some use cases of graph databases are as follows:

Fraud detection – A graph database is capable of classy fraud prevention. With its help, a person can utilize relationships for buying transactions in some near-real time. With a fast graph query, people can detect that. Graph databases help a person in detecting the patterns of relationship better, like several people linked with one personal email address or several people who share a similar IP address though residing in various physical addresses.

Recommendation engines – A graph database is an excellent choice for a recommendation application. With its help, you can preserve graph relationships between some information categories, friends, customer interests, and purchase history. A person can utilize a highly obtainable graph database for making product recommendations to the users grounded on which items are bought by others who do follow a similar purchase history. Again, you can also recognize people who have got a friend in common though they do not know each other.

The Features of Graph Database

The term “graph” has emerged from the utilization of this word in mathematics. It is useful for describing a set of nodes and each contains information and that too with some labeled edges or relationships between the nodes.

A graph database works by preserving the relationships with the data. These databases not only preserve the relationships between some components natively but also make queries relating relationships easy and fast.

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What Makes Graph Databases Exclusive?

Many databases possess similar features but graph databases possess some things that turn them exclusive. A couple of properties that every graph database technology must have are:

  • Graph storage – A few graph databases utilize native graph storage which is particularly designed for storing and managing graphs whereas others use columnar, relational or some object-oriented databases.
  • Graph processing – A native graph processing is an effective means to process data as connected nodes point to one other physically in the database.

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