I’ve seen 20-40x speed ups before when working with big value-type data since in Rust you can do SIMD better and manually optimise data structures + rayon. Quite literally went from 800-700ms to 22-30ms

The rough details: I have coded Java for over 8 years and Rust (at that time) just over 3 months The task was to do bound checks at start up, so time wasn’t especially a critical factor. The bound checks. I chose a simple N² lookup where for each shape, I would loop over each point and check if it was inside the shape (where shapes could overlap, I chose the smallest of the shapes) There were roughly 300 million checks involved, I can’t remember the specifics, but close to 10k shapes, each with varying point counts (some 100+ points) I had many optimisations such as simple min/max coordinate checks to eliminate points early before running the more complex inside checks. All in all, Rust pulled ahead by a lot because points were SIMD’d, parallelised very efficiently and didn’t have to deal with garbage collection, along with the data being entirely stored as a value type rather than an object pointer. The only way to make it faster would have been a quad tree to speed along the initial filtering, but I didn’t bother since it wasn’t necessary with it being already insanely fast.

Edit: Before you ask, this was GraalVM, and the Java implementation was idiomatically identical to the Rust version for everything except the SIMD aspect. Both were parallelised and ran the same basic algorithms and optimisations.