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> Recursive queries will not scale to handle _very_ large edge tables

What do you consider large ? We have a 12-year old telco application with a few million objects in Neo4J, doing fault impact calculations... Would PostgreSQL handle that easily nowadays ?

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My hunch is that a few million objects is pretty tiny these days - you could probably write a script to import all of them into PostgreSQL in a few minutes and try it out yourself to see how it behaves.

I tried it against SQLite. I got ChatGPT to write me a script that would insert 1m edges and 1m nodes:

https://gist.github.com/simonw/c16ce01244760e186a3a0aa3fee04...

Then I ran that query again and it seems to return results in about 80ms:

https://lite.datasette.io/?sql=https://gist.github.com/simon...

Not very realistic example, you need to be requesting some actual fields across nodes and doing some filtering on at least strings and dates, maybe geo areas as well.

Go ahead and try it! I've documented all of the tools you need to run some detailed experiments against SQLite entirely in your browser here.

It depends a lot on how connected the graph is and whether you can fit it in memory.

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