If you google the best programming languages for fintech, you will get a lot of different views. Many surveys give statistics with Python or Java topping the charts of the in-demand technologies. Some articles mention Go, C++, and Kotlin. So, what is number one? The truth is that each language is a smart choice if properly applied. This article will share our insights on fintech apps and guide you through the well-tried solutions that we use in our projects.
For more than 20 years, Java has been the primary language of fintech programmers. Banks and other financial institutions use it to build their complex software products. What is the reason for such long-lasting fame? First of all, it is stability and safety. Java has a wide range of features that make Java apps secure:
- Forcible runtime limits through Java Virtual Machine
- Security manager that isolates suspicious code from the healthy part of an executive program
- Security APIs that are easy to use
Another pro of Java is that it runs in a virtual environment. Due to this, it works on any device. You can quickly move your project to a different platform, both web, and mobile, keeping the code unchanged.
At Softensy, we make each banking app using Java. It is the primary language for backend development. One of the examples is the latest mobile banking EcoBank. It is a large, long-lasting project that we continually support and improve. Java is the best suited for projects with a long life. The language is strongly typed and structured and allows avoiding most errors at the compilation stage.
Python in fintech is one of the most popular languages today due to the flexibility and simplicity of the syntax. It supports modules and module packages, which contributes to modularity and code reuse. Standard libraries are available in both compiled and native form on all major platforms.
Python is cross-functional. It suits both backend and frontend development. Being dynamically typed, Python performs type checks during the execution time.
Many developers start their career path with this language because it is pretty easy to learn. Therefore, hiring a Python developer does not make a problem.
Now, you can come across many fintech apps built with Python. It is especially true for companies that work on short-term projects for small businesses. The above does not mean that you cannot write on Python extensive services. However, considering that Python is 1,5 times slower than Java, it is less in demand among enterprise-scale clients.
Go, also known as Golang, was first introduced by Google in 2009. Go creators’ central purpose was to make a simple language that, meanwhile, removes all the gaps of other languages. Golang is similar to Java. It has high performance and strict typification. It is also related to C in terms of syntax and speed.
The main benefit of Go is the ability to maintain many tasks at the same time. This feature is called concurrency. Highly concurrent apps can work with thousands of requests and are less likely to crash during peak load.
Which way does Go make it possible? It has so-called goroutines that are very lightweight and short. You can run millions of goroutines without performance issues. The sole condition – they must quickly do their job and exit.
Because of this, Go seems to be one of the best programming languages used in fintech for high-load systems. It serves enterprise applications that must process thousands of requests at once. So, if you need to create multi-threaded high-load server solutions, choose Go. That’s what we did in our mobile banking and CRM projects. In the mobile app, Go implements a microservice that sends push notifications and SMS to customers. In CRM, it is in charge of a contact center module, i.e., chatting with an operator.
C++ is an experienced player in the development world. It is a general-purpose language, which is also in demand in fintech. C++ is known for its program execution speed. By this parameter, it does not lag behind Java. That is why some companies prefer C++ banking app services.
Even though the language has recently dropped into the background, it is still considered the top choice for quantitative analytics and finance.
C++ is multi-thread, concurrent, and productive. At the same time, it is too complicated and has a low level of security. All this creates conditions to use the language in specific niches only. At Softensy, we rarely utilize it. Yet, we have some projects written in C++.
When you get to this point, you may wonder why previous fintech programming languages do not make a separate section “Backend.” I did this on purpose since each of them suits both backend and frontend development. Nevertheless, at Softensy, we mainly use them for the backend. We involve other technologies to create client-side since we believe they are more suitable for building modular architecture.
To make an interface, you need to describe how different parts of the interface look in each app’s state. React will effectively update and render only specific components when the data changes. Declarative interfaces make the code more predictable and much easier to debug.
Currently, React is much in demand. It is used in most trending projects in every field. Fintech is no exception. Users appreciate smart UI that allows glitchless money management in an app. React helps make it the easiest way.
Kotlin is a statically typed programming language that works on top of JVM. It is used for building Android apps and provides developers with simple and convenient tools that do not require much code.
In our opinion, Kotlin is not powerful enough for backend development, yet, it is a perfect choice for the frontend. At Softensy, we use Java for the big and complex backend. At the same time, we utilize Kotlin for app microservice architecture.
Swift is a multi-paradigm compiled programming language developed by Apple to co-exist with Objective C and be more resistant to errors. It has lightweight code and easy syntax that allows building iOS apps in a fast and straightforward manner.
Apple is continually working to improve Swift speed. Currently, the runtime performance of the language approaches C ++.
Swift is easy to understand for non-iOS developers. It is a big plus for large projects since all the participants can quickly figure out what the code means. In our company, we use Swift to make modular architecture for iOS apps.
Business apps make a specific area that combines finance and high technology. To deliver a safe product, we use various techniques and programming languages in fintech. At Softensy, we don’t have a one-box solution. For each project, we choose a custom technology stack that best meets the specifics of the product.
What is your take on R? Is it a good language to go with for fintech projects?
Vinayak, R is a great tool for analytics and statistics. However, we believe it makes no sense to use it for writing services of a general nature. Anyway, the tech stack depends on project specifics and should be discussed individually.
Best data science software course training institute in hyderabad
Very informative. Thanks a lot for sharing