Developer's Expedition into Rust for Market Interfacing and Financial Settlements
Chatting with Amandeep, Fintech Wizard at Hybrid Greentech Energy Storage Intelligence:
Have you ever wondered if Rust, the up-and-coming programming language championed for systems programming, could hold its ground in markets and financial settlements? Let's dive into Amandeep's journey of implementing Rust in mission-critical applications, and see how it fared.
From memory safety and standout concurrency to sizzling performance, Rust surely caught Amandeep's eye. But there were some hurdles, as with any romance—like incomplete XML digester libraries, the need for custom decimal type serialization, and the less-than-mature ecosystem for vital libraries.
Undeterred, Amandeep discovered the stability and ruggedness of Rust programs were too valuable for crafting unwavering, state-machine-driven architectures. Additionally, Rust's unbeatable replayability and verifiable computations ensured that financial calculations returned the same results every time—a must-have in the arena where regulatory compliance and auditability demand strict reproducibility.
The Rocky Road of Adopting Rust
1. Incomplete (and pesky) XML Digester Libraries
A-typical communication protocols in financial settlements rely on bulky XML frameworks. Although Rust can parse XML with libraries like roxmltree and quick-xml, they didn't quite cut it for complex digesting tasks. As a result, developers needed to pick up additional manual processing layers, and XML serialization and deserialization (serde-xml-rs) left a lot to be desired in comparison to Python or Java. Juggling deeply nested structures and mixed content required manual—and cumbersome—customizations.
2. Missing the Good Old DOM Library
Elements of the DOM (like Python's ElementTree) are a favorite tool for many developers, but they've vanished for Rust, which leaves devs with a hodgepodge of different crates and custom logic to achieve similar functionality.
3. Custom-made Decimal Type Serialization
In financial transactions, accuracy is paramount—and unlike other languages with built-in decimal support, Rust demands handwritten serialization/deserialization logic for decimal types, usually leaning on crates like rust_decimal to ensure precision.
4. Immature Ecosystem for Key Libraries
Although Rust's ecosystem is expanding, some fundamental libraries remain sub-par, such as the clickhouse crate, which lacks the extensive feature set available in Python. Similarly, while polars vies with pandas as a promising alternative, it still trails behind in terms of community support and versatility.
5. DataFrames and Analytics: A Mountain to Climb
In financial markets and settlements, analytics shape decisions. Rust lacks a robust pandas-like equivalent, pushing developers towards polars, which are still maturing. Although these libraries deliver performance perks, they require a different approach compared to the established Python analytics ecosystem, causing complex data-wrangling operations to balloon into verbose, low-level implementations.
6. Learning Curve: Laying a New Foundation
Rust's ownership model and strict compile-time guarantees force developers to reconsider their approach to programming. Though daunting initially, this constraint eventually proves advantageous as it instills disciplined programming practices. However, for teams transitioning from dynamic languages like Python or JavaScript, steep learning continues to pose a challenge and introduces unavoidable complexities with borrowing rules, lifetimes, and explicit type management.
Why Rust Shines in Market Integration
1. Stability, Replayability, and Robustness
With Rust, strong and consistent code execution is the norm. Memory safety and the elimination of data races guarantee that financial transactions execute with ironclad predictability, minimizing runtime errors and safeguarding potential security gaps. Rust's unrelenting type system likewise enables reliable computations, ensuring that identical inputs always yield the same outcomes—a vital factor in financial reconciliation and audits.
2. State Machines and Flexible Logic
Financial settlement systems function as finite state machines, proceeding via well-defined phases in transaction processing. Rust's enums, pattern matching, and type safety effortlessly encourage this design, helping yield clean, maintainable, and predictable code.
3. Performance Without the Worries of Garbage Collection
The absence of garbage collection in Rust translates into no unexpected pauses, making it suitable for latency-sensitive financial apps, where milliseconds can make a world of difference.
4. Concurrency at its Finest
Rust's threading model, anchored in ownership and send/sync traits, empowers developers to pen concurrent code without introducing data races. Concurrency in Rust is further elevated by Tokio, a battle-tested runtime that fuels event-driven programming for unparalleled efficiency.
5. Axum and Secure Web Frameworks
While Rust isn't limited to backend processing, it boasts some of the most robust and secure web application frameworks. Axum, built upon Tokio, offers a user-friendly and powerful method to create web applications, prioritizing security and performance. Unlike traditional web frameworks burdened with bloated middleware layers, Axum enables quick and highly efficient request handling, ideal for securing API endpoints for financial transactions.
6. SeaORM: Someone to Handle Database Interactions
One key area where Rust shines over languages like Java is the efficiency of its database ORM crates. SeaORM, an asynchronous ORM, drastically reduces memory consumption compared to traditional ORMs like Hibernate. While Java-based ORM layers often chew through gigabytes of memory, SeaORM guarantees minimal memory footprint without skimping on essential features like query building and database abstraction.
7. Effortless Integrations
Finally, the ability to interweave Rust with WebAssembly lends itself to seamless integrations with existing financial infrastructure. Legacy systems in financial institutions often rely on COBOL, Java, or C++, and Rust's FFI (foreign function interface) support allows for gradual migration, making the process less cumbersome.
Rust: A Love Story Worth Pursuing
Despite the steep learning curve, Rust has shown itself to be a force to be reckoned with in financial technology. The rigor results in dependable code, and its ecosystem is continually growing. Although devs may gravitate towards languages like Python for prototyping due to ecosystem gaps, the demand for unyielding, high-performance, and robust solutions brings Rust back into the equation when the stakes are high. The increasing investment in Rust-based tools, including database engines and analytics frameworks, signals a bright future for Rust in the enterprise.
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- Amandeep Midha's interest in Rust was sparked by its memory safety, standout concurrency, and sizzling performance, despite the challenges posed by incomplete XML digester libraries, the need for custom decimal type serialization, and the less-than-mature ecosystem for vital libraries.
- Rust's unbeatable replayability and verifiable computations ensured that financial calculations returned the same results every time, a must-have in Amandeep Midha's work with mission-critical applications, where regulatory compliance and auditability demand strict reproducibility.
- In his journey implementing Rust in financial settlements, Amandeep Midha faced numerous challenges, such as the lack of a DOM library, manual XML processing, and the need for custom-made decimal type serialization, due to Rust's less mature ecosystem.
