(Replying to PARENT post)

The backend scaling/complexity problems originate in the database, its kind of cute the way they put it: "Making the graph-oriented way of getting data fit over an SQL database can be tricky." Tricky vastly understates this: we are talking about ORM, the "vietnam of computer science"

Clojure ecosystem has an immutable database, Datomic, which is designed for functional programming and fully solves the impedance mismatch. Datomic "Pull queries" is essentially GraphQL – and even predates GraphQL by a year!

Unlike GraphQL, Datomic is also a real database, competitive with SQL and can express relational filters and joins. Datomic is designed for the read-heavy data modeling loads that, today, SQL (and mongo, etc) is used for in anger. https://www.datomic.com/

👤dustingetz🕑7y🔼0🗨️0

(Replying to PARENT post)

I love clojure and appreciate what Datomic brings to the table, but it seems like you need the whole package (clojure backend) in order for the benefits to pay off. GraphQL is a much less risky proposal for most companies, since it can be implemented more iteratively, and is storage-layer agnostic.

👤headcanon🕑7y🔼0🗨️0

(Replying to PARENT post)

Before clicking through, I never knew that datomic has dependancies on AWS specific services. That's a serious downside, for many cases.

👤SmirkingRevenge🕑7y🔼0🗨️0

(Replying to PARENT post)

Naming things is the Vietnam of computer science. I wrote a haiku for it:

A quagmire of bad decisions made in haste, haunting us— years later.

👤amsheehan🕑7y🔼0🗨️0