Does anyone know whether it’s possible to emulate a graph database with a relational by adding specific meta-data tables or indices? Emulate in the sense that you can do efficient graph traversals that drill along a path for a certain non-trivial depth.
Thanks, that’s helpful! Is this repeated querying essentially what graph databases do under the hood? Can this be more efficient than multiple joins? Also, what are RDF strategies?
Of course it can be done more efficiently… with a non-relational database xD
If you want performance look into real graph databases implementations. Optimizing a graph database over a relational database seems a waste of time IMHO. I may be mistaken.
If you haven’t read this, start here: https://en.wikipedia.org/wiki/Triplestore
You can do many common graph search operations in only one query using recursive CTEs (common table expressions). You should probably look into the documentation of your RDBMS because details may vary, but here’s an example from PostgreSQL’s documentation on recursive CTEs:
WITH RECURSIVE search_graph(id, link, data, depth) AS ( SELECT g.id, g.link, g.data, 1 FROM graph g UNION ALL SELECT g.id, g.link, g.data, sg.depth + 1 FROM graph g, search_graph sg WHERE g.id = sg.link ) CYCLE id SET is_cycle USING path SELECT * FROM search_graph;How do sql query engines backed by S3 like Trino (Athena) behave for euch queries?
I don’t know. But recursive CTEs habe been part of the standard since SQL:1999, so if they advertise compliance with SQL:1999 or a newer version of the standard, they should at least be able to execute the query. To find out whether they do so efficiently, you could do an experiment (remember most SQL engines allow you to look at the query plan for a given query) or read their documentation.