Monthly Archives

Discovering an appropriate backend for Swift applications is paramount for Apple developers to build flexible, scalable, and highly tailored applications.

Swift is a robust, multi-paradigm, and compiled scripting technology launched in 2014. Apple completely endorses this general-purpose programming language to build lightning-fast macOS, watchOS, iOS, tvOS, and iPadOS applications. 

Swift’s simple learning curve, regular updates, stability, and beginner-friendly nature make it an ideal option for many Apple programmers.

However, using this iOS language with the right backend solution is equally essential to achieve maximum outcomes. 

That is why this article will share a variety of Swift backend options and their features. We will also give a quick overview of setting up a Swift app’s backend. 

Let’s kick things off.

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Open-source Backend as a Service (BaaS) solutions have streamlined the development of mobile and web applications in the past few years.

This cloud computing model confers a complete set of server-side functionalities to build and deploy backends robustly. That is why the popularity of BaaS platforms is climbing.

According to a forecast report by Allied Market Research, the Backend as a Service (BaaS) market will hit 28.7 billion USD at the end of 2032. This value was 3.1 billion USD in 2022. It signifies the growth of the BaaS industry with a CAGR of 25.3% in ten years.

Similarly, MarketsandMarkets projects the BaaS market size to be around 9.2 billion USD by 2028. This report anticipates a CAGR of 17.5% from 2023 to 2028.

However, businesses and dev teams prefer using open-source BaaS platforms because of their benefits. Some prominent features are no vendor lock-in, cost efficiency, flexibility, easy customization, and community support.

So, you must consider this guide if you are a backend engineer or a company looking for a Backend as a Service (BaaS) open-source solution.

We will thoroughly discuss the leading options, traits, and perks of using open-source cloud computing platforms.

Let’s begin!

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AI coding assistants are a type of software development tool intended to make coding processes faster and easier. These assistants rely on artificial intelligence to help developers generate, fix, or adjust code. They usually integrate with popular IDEs (development environments) and work in real time. 

A major function of AI coding assistants is to offer suggestions for code completion, which is possible given their ability to understand the context of code. These assistants typically use large language models (LLMs) to analyze large code repositories and identify relevant patterns, and solutions for a given code snippet or function. 

AI coding assistants are especially useful for speeding up the process of writing code through automation. Developers often use them to carry out repetitive or simple but time-consuming tasks, or to highlight issues. However, they cannot reliably replace the human input and still require some level of expertise to create accurate and safe code.

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