Datafun: a functional query language
summary
Datafun claims a minimal bridge between functional languages and database queries by adding set comprehensions and explicit fixpoints to a pure total language, letting recursive Datalog-style queries become ordinary expressions. The prototype applies a known database optimization (semi‑naive style) and a recent extension: static incremental derivatives for higher‑order values to update fixed‑point iterations. Implementation lives as notebooks on GitHub, early but demonstrating the idea and a path toward faster incremental evaluation.
AI-written summary · about
chapters (6)
- 0:00Start
- 7:25Queries as set comprehensions finding siblings
- 9:21Loop reordering
- 16:44Datalog in a nutshell
- 27:48Three problems
- 33:19Finding fixed points faster with derivatives
related talks
32mReactive Datalog for Datomic
27mFunctional Programming on Top of SQL Engines
17mFixpoints for the Masses: Programming with First-Class Datalog Constraints
42mA Practical Functional Relational Architecture
52mData Over Code: A Short Hyperbole
47mFunctional Programming in the Cloud: Simpler Application Development with Datomic Cloud
52mEnhancing Datalog for Datomic
43mDatalog all the way down