Searching on Your Location with Atlas Search and Geospatial Operators

When thinking about full-text search, text and other string data is probably the first thing to come to mind. In fact, if you’ve been keeping up with my tutorials, you might remember Building an Autocomplete Form Element with Atlas Search and JavaScript or Visually Showing Atlas Search Highlights with JavaScript and HTML, both of which were on text search examples in MongoDB Atlas Search.

Being able to use natural language search on text data is probably one of the most popular use-cases, but there are scenarios where you might need to narrow the results even further.

Let’s say you’re building a restaurant review application like Yelp or a bed and breakfast booking system like Airbnb. Sure, you’ll enter some kind of text criteria for what you’re looking for, but there’s also a location aspect to it. For example, if you want to find a place to get a cheeseburger within walking distance of your current location, you probably don’t want your search results to contain entries from another country. This is an example of a geo search, where you would want to return results based on location coordinates.

In this tutorial, we’re going to see how to use Atlas Search and the compound operator to search based on text entered and within a certain geographical area. For the text entered, we’ll use the autocomplete operator, and for the geospatial component, we’ll use the geoWithin operator.

Getting Started with the Realm SDK for Unity

Did you know that MongoDB has a Realm SDK for the Unity game development framework that makes working with game data effortless? The Realm SDK is currently an alpha release, but you can already start using it to build persistence into your cross platform gaming projects.

A few weeks ago I streamed about and wrote about creating an infinite runner type game using Unity and the Realm SDK for Unity. Realm was used for storing the score between scenes and sessions within the game.

There were a lot of deep topics in the infinite runner (think Temple Run or Subway Surfer) example, so I wanted to take a step back. In this tutorial, we’re going to spend less time making an interesting game and more time including and using Realm within a Unity project.

Build an Infinite Runner Game with Unity and the Realm Unity SDK

Did you know that MongoDB has a Realm SDK for the Unity game development framework that makes working with game data effortless? It’s currently an alpha release, but you can already start using it to build persistence into your cross platform gaming projects.

A popular game template for the past few years has been in infinite runner style games. Games such as Temple Run and Subway Surfers have had many competitors, each with their own spin on the subject. If you’re unfamiliar with the infinite runner concept, the idea is that you have a player that can move horizontally to fixed positions. As the game progresses, obstacles and rewards enter the scene. The player must dodge or obtain depending on the object and this happens until the player collides with an obstacle. As time progresses, the game generally speeds up to make things more difficult.

While the game might sound complicated, there’s actually a lot of repetition.

In this tutorial, we’ll look at how to create our own infinite runner game with Unity and C#. We’ll look at important concepts such as object pooling and collision, as well as data persistence using the Realm SDK for Unity.

Update Array Elements in a Document with MQL Positional Operators

MongoDB offers a rich query language that’s great for create, read, update, and delete operations as well as complex multi-stage aggregation pipelines. There are many ways to model your data within MongoDB and regardless of how it looks, the MongoDB Query Language (MQL) has you covered.

One of the lesser recognized but extremely valuable features of MQL is in the positional operators that you’d find in an update operation.

Let’s say that you have a document and inside that document, you have an array of objects. You need to update one or more of those objects in the array, but you don’t want to replace the array or append to it. This is where a positional operator might be valuable.

In this tutorial, we’re going to look at a few examples that would benefit from a positional operator within MongoDB.

Zap, Tweet, and Repeat! How to Use Zapier with MongoDB

I’m a huge fan of automation when the scenario allows for it. Maybe you need to keep track of guest information when they RSVP to your event, or maybe you need to monitor and react to feeds of data. These are two of many possible scenarios where you probably wouldn’t want to do things manually.

There are quite a few tools that are designed to automate your life. Some of the popular tools include IFTTT, Zapier, and Automate. The idea behind these services is that given a trigger, you can do a series of events.

In this tutorial, we’re going to see how to collect Twitter data with Zapier, store it in MongoDB using a Realm webhook function, and then run aggregations on it using the MongoDB query language (MQL).

Capturing Hacker News Mentions with Node.js and MongoDB

If you’re in the technology space, you’ve probably stumbled upon Hacker News at some point or another. Maybe you’re interested in knowing what’s popular this week for technology or maybe you have something to share. It’s a platform for information.

The problem is that you’re going to find too much information on Hacker News without a particularly easy way to filter through it to find the topics that you’re interested in. Let’s say, for example, you want to know information about Bitcoin as soon as it is shared. How would you do that on the Hacker News website?

In this tutorial, we’re going to learn how to parse through Hacker News data as it is created, filtering for only the topics that we’re interested in. We’re going to do a sentiment analysis on the potential matches to rank them, and then we’re going to store this information in MongoDB so we can run reports from it. We’re going to do it all with Node.js and some simple pipelines.

Manage Game User Profiles with MongoDB, Phaser, and JavaScript

When it comes to game development, you’re almost always going to need to store information about your player. This information could be around how many health points you currently have in the game or it can extend beyond the game-play experience and into details such as the billing information for the person playing the game. When we talk about this type of data, we’re talking about a user profile store.

The user profile has everything about the user or player and doesn’t end at health points or billing information.

In this tutorial, we’re going to look at creating user profiles in a game that leverages the Phaser game development framework, JavaScript, and MongoDB.