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Another type of NoSQL database are graph databases, which are based on modeling entities and relationships as nodes and links in a graph or network. Social networks are a good example of a use case for graph databases. People could be modeled as nodes in the graph, and relationships between people are links, also called edges. For example, Figure 1.2 shows an example graph of friends showing Chengdong with the most friends, 6, and Lem with the fewest, 1.

Figure 1.2 Example graph of friends

Data is retrieved from a graph using one of two types of queries. One type of query uses SQL-like declarative statements describing patterns to look for in a graph, such as the following the Cypher query language. This query returns a list of persons and friends of that person’s friends:

MATCH (n:Person)-[:FRIEND]-(f) MATCH (n)-[:FRIEND]-()-[:FRIEND]-(fof) RETURN n, fof

The other option is to use a traversal language, such as Gremlin, which specifies how to move from node to node in the graph.

GCP does not have a managed graph database, but Bigtable can be used as the storage backend for HGraphDB (https://github.com/rayokota/hgraphdb) or JanusGraph (https://janusgraph.org).