If you are a fan of Dark Netflix Series, here is a graph database for fun. Graph analysis : this is where the real fun is, now you can perform queries and see how these characters are related to each other, in which timeline they have traveled, and see a brief description of their activity in that timeline by cypher queries which are here.
Dark series is one of the thriller, sci-fi series which has time travel to make things more complex than they were. Each character is related to others through time travel which makes the relationship between them too complex and graph databases are perfect use cases to reveal the insight of such connected data and believe me it's fun to work on such complex data and relations.
So let’s begin from the beginning Prerequisite: Install the [neo4j desktop app], create a local graph, and get ready for next. Graph modeling: This is the core of graph database where we design the schema which tells the relation between different nodes forming the relationship to carry out business logic, the simpler the schema, simpler is graph queries.** But the most complex thing is to make things simpler. **
In this article, we first explained some reasons to migrate graph databases from SQL Server into Neo4j. Then we provided a step-by-step guide to migrate Nodes and edges using C#. The code provided may or may not be optimal. I published it on GitHub, so feel free to use it or improve it.
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We will explore the basic concepts of a Graph Database and then look at some examples of graph data modeling and querying by using Neo4j graph database
Collect Twitter data, store them in a graph database, and analyze them using graph algorithms.