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An introduction to a SQL Server 2017 Graph database

What is a graph database?

A graph is composed of two elements: a NODE (vertices) and an EDGE (relationship). Each node represents entities, and the nodes are connected to one another with edges; these provide details on the relationship between two nodes with their own set of attributes and properties.

The graph database can be defined as the data structure representation of an entity modeled as graphs. It is derived from the graph theory. The data structures are the Node and the Edge. The attributes are the properties of the node or the edge. The relationship defines the interconnection between the nodes.

Relationships are prioritized in graph databases, unlike other databases. Therefore, no data inference using foreign keys or out-of-band processing is needed. We can build sophisticated data models simply by assembling abstractions of nodes and edges into a structure. Given the priority for relationships over data, the development stack receives the biggest value here.

In today’s world, relationship modeling requires more sophisticated techniques. SQL Server 2017 offers graph database capabilities to model relationships. Graph DB has nodes and edges—two new table types NODE and EDGE. And a new TSQL function called MATCH(). The Node and Edge (relationships) represent entities of the graph database. And since this capability is built into SQL Server 2017, already-existing databases don’t have to be ported to another system, so to speak.

Further reading…

Graph database

Stay tuned for more updates on this topic….


PowerSQL By Prashanth Jayaram

Technology enthusiast with 7+ years of experience in Database Technology. I am Microsoft Certified Professional with certificates of OCA, MCP, MCTS, MCITP developer, MCITP administration and backed with a degree in Master of Computer Application. My expertise lies in T-SQL programming, Replication, PowerShell and Performance Tuning. Hobbies are Drawing, playing soccer and listening to Melodies songs.

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