In iOS, WebSockets enable real-time communication between a client (an iOS app) and a server. Unlike traditional HTTP connections which are stateless, short-lived and request data on demand, WebSockets use a single long-lived connection to send and receive data simultaneously. This significantly reduces response times which is crucial for apps that rely on instant updates and live data to support functions such as chat and multiplayer games.

On top of their industry-leading cloud infrastructure, Amazon Web Services (AWS) offers more than 15 cloud-based analytics services to satisfy a diverse range of business and IT use cases. For AWS customers, understanding the features and benefits of all 15 AWS analytics services can be a daunting task - not to mention determining which analytics service(s) to deploy for a specific use case.

Let’s start at the very beginning, so it’s clear exactly what we’re talking about here – in Swift, networking is the process of sending and receiving data between an iOS application and a remote server or another device over the internet.

If you’re building for mobile apps, you need Realm in your life. It’s specifically designed for mobile devs and even though it’s available on multiple platforms, it’s typically used to develop iOS apps, using Swift. Built on top of SQLite Realm Swift is a very high-level abstraction layer that simplifies database operations for the developer. Today we’re going to unpack it, with a guide that drills so far down into the subject, it’s practically in Australia.

Core Data enables us to manage the model layer of an Apple application. This layer is a crucial part of our app’s engine room, allowing the pretty bits at the front end to interact with the data and business logic at the back. We love Core Data because it provides a powerful database technology framework, and it’s built on top of the SQLite management system, which requires zero configuration or external storage space.

Can DataOps help data consumers reveal and take action on powerful product insights hidden in operational data? For many companies, the answer is yes! The emerging practice of DataOps applies Agile development principles and DevOps best practices (e.g. collaboration, automation, monitoring and logging, observability) to data science and engineering, making it faster and easier for organizations to uncover valuable product insights that enable innovation.

Introduced in iOS 14, App Clips allow users to quickly access a specific feature within an application (e.g. paying for parking or ordering a coffee) without downloading the full app. So they allow our users to interact with our apps on their terms, creating more targeted interactions that benefit us as well as them.

Introduced in 2023, SwiftData is the latest addition to the range of database framework options in Swift, Apple’s primary programming language for iOS. Built on top of Core Data, two levels above SQLite, it’s great for simplifying our persistent stores and it allows us to use declarative code, which is a really useful time-saver.

The term ‘data persistence’ refers to data that remains available, even when the program that created it is idle, sleeping or unable to open. In many cases, our iOS apps need to provide support around the clock, so we need our data to be ‘always on’ – even when the apps themselves are not.

Streaming analytics is an invaluable capability for organizations seeking to extract real-time insights from the log data they continuously generate through applications and cloud services. To help our community get started with streaming analytics on AWS, we published a piece last year called An Overview of Streaming Analytics in AWS for Logging Applications, where we covered all the basics.