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Which AWS programming language is best for our project?
AWS developers can choose between a variety programming languages, including Microsoft, .NET, Java and Python. How do they differ and should we use them to develop applications?
IT teams can build applications using several AWS programming languages, including Microsoft .NET, Java, Python,...
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Ruby, Node.js and PHP. These languages can be divided into two categories: statically compiled and strongly typed or dynamic and interpretive. Knowing which one is right for your AWS project means understanding the problems you need to solve as well as your project timeframe.
Statically compiled and strongly typed programming languages contain well-documented code with clean interfaces that provide compile-time errors rather than runtime errors. However, it takes longer to build software using this type of language. On the other hand, dynamic and interpretive languages simplify the development phase, including support assistance for sophisticated debugging and refactoring functionality. This ensures the delivery of high-quality code that's naturally suited for rapid AWS development projects.
When choosing an AWS programming language for your project, it's important to first identify problems with the domain and the local ecosystem. To do this, conduct research to identify what languages have solved similar types of business problems. If you're IT staff that's trained specifically for the programming language you choose or application type you're building, consider outsourcing work to a developer or third party.
The next step is to select an AWS programming language that allows for the quickest app development. Don't forget to take into account the business case and types of end users who will interact with the application. For example, if an application integrates heavily with Microsoft Office and other Windows apps, .NET might be the best choice. But if the application needs to perform functions such as weather forecasts, Python might be a good option because of its math library and ability to scale with Hadoop in the cloud.
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