I am trying to create a scalable platform. Without having best practices to learn from, I had to discover what that required while trying to make the most of Rust. The discovery process involves many iterations of trying approaches out until a decent one emerges.
On the other hand, once I laid the tracks down, I found my usual hindrances to productivity: business logic and data modeling.
I am much more productive with Rust and raw SQL parameter binding than Python with SQLAlchemy query builder. Evidently, the costs associated with using an orm are greater than the benefits for someone who is fluent in SQL. Learning a dsl and then fighting the dsl and then asking for help repeatedly, just to accomplish the same task and no more, is a really bad use of time.
I built an API in Python and SQLALchemy. Originally, it was built in Flask and Flask-SQLALchemy, but I eventually decided to migrate it to Falcon + SQLService and saw greatly improved response times from my API (hosted on AWS Lambda). Am I likely to see as significant improvements from a switch to Rust + raw SQL queries?
I am kindly looking for a reason to learn Rust. :) With the recent improvements to AWS Lambda, a Rust run-time is a reality and I am open to migrating the project once again for any additional speed improvements.
I largely agree although I've recently discovered the beauty of re-usable, type-checked sub-clauses by composing C# lambda expressions for Entity Framework using e.g., AndAlso():