Transforming Graph Models

Learn why graph serialization is important and how we are going to achieve it.

Overview

How do we repurpose graphs from one model type to another? We’ll look at how to connect different graphs as well as some various graph transforms. We’ll also review how Elixir supports concurrency through supervision networks.

By now, we’ve looked at a bunch of different graph models, but we skimmed over how these could be serialized and saved to our graph store. Each of these models can be expressed in its own various ways.

We’ll now talk about some ways to serialize graphs and also list the pros and cons of using common formats such as CSV for exchanging graph data.

We’ll then go on to work through a more robust solution with the Neo4j plug-in neosemantics (n10s), which supports importing and exporting RDF graphs into and out of a property graph store, and querying RDF graph models using the Cypher query language.

We’ll also briefly touch upon the topic of federated querying—that is, querying against multiple graph databases.

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