I ended up with Neo4J despite trying Memgraph, TigerGraph, and others, it seemed that Neo4J was the most mature and widely supported. It also was stable in my limited infrastructure that I was using.

The analytics console looks very much like the query console with the exception of the panels on the right. This is where you can map data structures from the local or remote Couchbase collections as sources. The analytics service makes a copy of the original data, and provides the ability to index it separately from the original source.

If you're a software engineer, there are various SDK's and connectors available. On the other hand if you just want to look at document content, either the built-in "Query" section on the Couchbase console, or a third-party tool that has a driver to connect.

The load process for the documents is reasonably simple. It consists of a single Python script which reads a targeted number of JSON documents from the input location, and runs a number of functions to extract data that map to the buckets, scopes, and collections that I had shown in the previous posts.