A Comparison of NoSQL Database Management Systems and Models(Part III)

Graph Databases

Graph databases are a subcategory of record stores such that they contain data in records rather than requiring data to conform to a predefined schema. Chart databases, on the other hand, provide an extra dimension to the record model by emphasizing the relationships between different records. It’s crucial to consider the following concepts in order to comprehend the idea of graph databases:

Node: In a graph database, a node is a representation of an individual object. In a relational database, it’s roughly equivalent to the definition of a record or row, and in a document shop, it’s roughly equivalent to the concept of a document. A node, for example, may represent a single performer or band in a graph database of music recording artists.

A property is a piece of knowledge that is specific to each node. Using the recording artist as an example, certain assets may be “vocalist,” “jazz,” or “platinum-selling artist,” depending on the database’s needs.

An edge, also known as a graph or association, is a central term in graph databases that distinguishes them from RDBMSs and record stores. It is the description of how two nodes are connected. There are two types of edges: directed and undirected.

Because of the way graph databases bind and group similar pieces of information, such operations are much easier to execute. These datasets are often used in situations where it’s critical to be able to derive insights from the relationships between data points, including in environments where the knowledge accessible to end users is dictated by their social networks, such as in a social network.

Conclusion

We’ve only covered a handful of the NoSQL data types in use today in this article. Some NoSQL architectures, such as object stores, have seen differing degrees of adoption over time, but they remain viable alternatives to relational models in some situations. Others, such as object-relational databases and time-series databases, combine aspects of relational and NoSQL data structures to provide a kind of middle ground between the two extremes.

The NoSQL database category is incredibly wide, and it is still evolving today. If you want to read more about NoSQL database management systems and definitions, we recommend that you look at our NoSQL-related knowledge collection.