Since today is a saturday let’s review a fun feature – ROI (return on investment) calculator. That many sound like a boring subject, but we sure tried to make it fun. Indeed, if you are a developer and are tasked to figure out how a product or a service can save money, it may be a daunting task. Certainly not with Backendless. First of all you can start with our service at no cost all – the Backendless free plan is very generous with unlimited API calls and no request per second throttling. On top of this, Backendless will tell you how much money you’re saving just by using it. Here’s how you can find out:
Loading data objects from the Backendless persistent storage is a fundamental operation a large majority of the online/mobile applications require. Backendless data retrieval API is simple, yet very powerful. As you will learn in the course of this series, the API provides the following capabilities:
In this post we continue our mission to build a restaurant to-go order app. So far we have put together UI mockups for the future Backendless application, and designed data schema for all application’s data entities. At this point we got very close to the coding part. As the title of this article suggests, we will be generating some code, but before we do it, let me describe a core principle of the client-server integration with Backendless.
As soon as you have data in a persistent storage, the question of searching would be one of the first to come up. Indeed, how can you query the backend for data? We considered multiple options and settled on the most popular one – SQL. However, we had to take a few shortcuts to allow SQL searches – the most notable is you can use only the “where” part of an SQL query to search for your data. Consider the following data table:
Backendless can create tables when you store object hierarchies from a client application. Also, I described how to manually create data tables using Backendless console. Finally, there is one more approach which makes table creation as simple as it gets. The approach is by uploading a file which contains schema definition for every table. The schema definition may include data types for all columns, including the ones for relations. As a part of my quest to build a restaurant to-go order app, I created all the tables in my Backendless backend. I used the schema export feature (to be discussed in the future) which generated for me a ZIP file with the schema definitions for all the tables used by the app.
A few posts ago I published a proposed schema for the database design for a sample app which can process mobile to–go orders. As the first step in building the application, I put together a rather simplistic user interface mockup for the future app. You can see the mockup below:
The next step will be a series of posts where we design the client-side of the app for Android and iOS. Additionally, we will be exploring and reviewing various Backendless features as we move along.
In my post yesterday I showed how to declare relationships between tables. Once a relationship is in place, specific objects stored in the tables may be linked with each other. This linkage may be expressed through the code, where the instances of classes reference each other through the composition method. However, there are scenarios where these relationships may need to be created directly in the storage system. Backendless console is the development tool that lets you manage it using a graphical interfaces. The types of relationships you can build by hand can be either one-to-one or one-to-many. As a result of establishing a relationship between any two or more objects, you can retrieve the related objects using the API. For instance, in the example below a restaurant object will have a relationship with one or more location. When the restaurant object is retrieved via an API call, all the related locations can be retrieved as well.
In my of my previous posts I described how to add columns/properties to a Backendless table/class using console. The types of properties reviewed in that post were all primitive: string, numbers, dates or boolean values. In addition to these data types, Backendless also supports relationships between objects stored in its persistent storage. These relationships are classic composition types in the object-oriented world. That means a table may declare a property (column) which references either one or a collection of objects from another (or the same) table. When these objects are materialized on the client-side (assuming the language supports object-oriented programming), the properties simply reference related objects.
When a user registers for your app, it is quite common to make sure he provided a valid email address. Typically this is done by sending a URL to the user’s email address and ask him to follow the link. Once the link is opened in a browser, it serves as a confirmation of a valid email address. This is rather standard functionality of an application’s backend. Backendless makes it very easy to configure this behavior for any application powered by our platform. To configure email confirmations for your app: