So, I mean, good luck.
>Today, the Python backends to the web services communicate directly with PostgreSQL via SQLAlchemy, but it is my intention to build out experimental replacement backends which are routed through GraphQL instead. This way, the much more performant and robust GraphQL backends become the single source of truth for all information in SourceHut.
I wonder how adding a layer of indirection can significantly improve performance. If I were writing this service, I would go all in on GraphQL and have the frontend talk to the GraphQL services directly rather than routing the requests from Python through to a GraphQL service then presumably to PostgreSQL.
Perhaps I am missing something. Indeed good luck to Drew here.
But claiming some nebulous backend that's more performant and robust than Postgres is like, WTF? Are you using an actual GraphDB like Neo4J? Are you putting a graph frontend on Postgres like PostGraphQL? None of the post really makes any sense because GraphQL is a Query Language, not a data store. What are the CAP theorem tradeoffs in the new backend? What does more robust mean? What does more performant mean? This is a source control app. Those tradeoffs are meaningful.
There seems to be a lot of conflation between API design and data store and core programming tools all mixed into a big post that mostly sounds to me like, "I don't get how to make this (extremely popular and well-known platform that drives many websites 10000x my size) work well, so I'm trying something different that sounds cool."
Which, again, the author has always said this is an experiment, and that's cool. But the conceptual confusion in the post makes me think that moving away from boring tools and trying new tools is not going to end up going well.
But this is a source control app, and it's hopefully backed up somewhere besides sourcehut so it should be fine if he needs to backtrack.
GraphQL isn't particularly "graphy". Its name sucks. But don't worry, plenty of half-techy middle managers are out there making the same mistake and going "we do graph things, why don't you guys look into this GraphQL thing that's getting so much buzz?" It's not a great fit for graph operations, in fact. Not more than SQL, certainly.
As for N4J in particular, don't count on that to improve performance even if you're doing lots of graph stuff. Depends heavily on your usage patterns and it's very easy to modify a query in a way that seems like it'd be fine but in fact makes performance fall off a cliff. OTOH Cypher, unlike GraphQL, is a very nice language for querying graphs.