When working with Backendless, data you accumulate can easily be exported. The inner workings of the export process itself are quite complicated since it takes into account all the relationships within your data. For you, the user, this process is in fact quite simple.
Backendless provides a powerful and convenient tool for working with Backendless services through REST API (read all about our REST APIs in the documentation here). In case you need to quickly test a REST API’s functionality, another tool may come in handy for you – the Backendless REST Console.
When working with data, particularly user-submitted data, you often need to validate it. For example, if we are creating a database in which there is a “site” field and corresponding IP address field, it would be very useful to ensure that the data written to these fields is in the appropriate format.
Today we are going to demonstrate how to create and save new data objects using the very convenient REST Console in Backendless. The console lets you easily test your REST APIs prior to deployment.
Today we are going to walk you through the process of allowing users to register and log into your app using their Google account. The best way to showcase this is to walk through the Registration and Login example app available in the Code Generation section of your Backendless Console.
Today, we are going to look at a useful and interesting, but hidden, feature of Backendless. This function will give us the ability to create a multi-column table schema with a single query.
Today we are going to demonstrate how to create a simple event handler to track subscriber statistics on your various messaging channels. This gives you the ability to easily track the number of subscribers for each of your channels to help you manage channel load and gauge user interest in specific topics. Used in combination with API usage…
When analyzing data, you may need to know the average salary of all employees, the quantity of goods in stock, the number of individual items in stock, the maximum or minimum cost, and so on. These tasks are easily handled with aggregate functions. Aggregate functions perform calculations using the values in a column in order…