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).

Developing a Side-Scrolling Platformer Game with Unity and MongoDB Realm

I’ve been a gamer since the 1990s, so 2D side-scrolling platformer games like Super Mario Bros. hold a certain place in my heart. Today, 2D games are still being created, but with the benefit of having connectivity to the internet, whether that be to store your player state information, to access new levels, or something else.

Every year, MongoDB holds an internal company-wide hackathon known as Skunkworks. During Skunkworks, teams are created and using our skills and imagination, we create something to make MongoDB better or something that uses MongoDB in a neat way. For Skunkworks 2020, I (Nic Raboy) teamed up with Barry O’Neill to create a side-scrolling platformer game with Unity that queries and sends data between MongoDB and the game. Internally, this project was known as The Untitled Leafy Game.

In this tutorial, we’re going to see what went into creating a game like The Untitled Leafy Game using Unity as the game development framework and MongoDB Realm for data storage and back end.

Client-Side Field Level Encryption (CSFLE) in MongoDB with Golang

One of the many great things about MongoDB is how secure you can make your data in it. In addition to network and user-based rules, you have encryption of your data at rest, encryption over the wire, and now recently, client-side encryption known as client-side field level encryption (CSFLE).

So, what exactly is client-side field level encryption (CSFLE) and how do you use it?

With field level encryption, you can choose to encrypt certain fields within a document, client-side, while leaving other fields as plain text. This is particularly useful because when viewing a CSFLE document with the CLI, Compass, or directly within Altas, the encrypted fields will not be human readable. When they are not human readable, if the documents should get into the wrong hands, those fields will be useless to the malicious user. However, when using the MongoDB language drivers while using the same encryption keys, those fields can be decrypted and are queryable within the application.

In this quick start themed tutorial, we’re going to see how to use MongoDB field level encryption with the Go programming language (Golang). In particular, we’re going to be exploring automatic encryption rather than manual encryption.

Visually Showing Atlas Search Highlights with JavaScript and HTML

When it comes to finding specific words or phrases within text, you’re probably going to want to use a natural language search option like full-text search (FTS). Sure, you could probably create a complicated and difficult-to-maintain set of regular expressions to search within text, but that is an option that most developers don’t want. Not to mention it won’t cover the full scope of what a natural language processor typically accomplishes.

In a previous tutorial titled Building an Autocomplete Form Element with Atlas Search and JavaScript, I wrote about searching for recipes, as they are being typed, in MongoDB Atlas using the autocomplete operator. While this tutorial accomplished the job quite well, it didn’t elaborate on what exactly was being matched for any given term.

In this tutorial, we’re going to see how to use Atlas Search and work with the highlight data to visually show any matches on the terms in a user facing application. Highlighting is a powerful tool with Search to allow your users to find the exact text that they want in its proper context.

Sending and Requesting Data from MongoDB in a Unity Game

Are you working on a game in Unity and finding yourself needing to make use of a database in the cloud? Storing your data locally works for a lot of games, but there are many gaming scenarios where you’d need to leverage an external database. Maybe you need to submit your high score for a leaderboard, or maybe you need to save your player stats and inventory so you can play on numerous devices. There are too many reasons to list as to why a remote database might make sense for your game.

If you’ve been keeping up with the content publishing on the MongoDB Developer Hub and our Twitch channel, you’ll know that I’m working on a game development series with Adrienne Tacke. This series is centered around creating a 2D multiplayer game with Unity that uses MongoDB as part of the online component. Up until now, we haven’t actually had the game communicate with MongoDB.

In this tutorial, we’re going to see how to make HTTP requests from a Unity game to a back end that communicates with MongoDB. The back end was already developed in a tutorial titled, Creating a User Profile Store for a Game With Node.js and MongoDB. We’re now going to leverage it in our game.

Creating a User Profile Store for a Game With Node.js and MongoDB

When it comes to game development, or at least game development that has an online component to it, you’re going to stumble into the territory of user profile stores. These are essentially records for each of your players and these records contain everything from account information to what they’ve accomplished in the game.

Take the game Plummeting People that some of us at MongoDB (Karen Huaulme, Adrienne Tacke, and Nic Raboy) are building, streaming, and writing about. The idea behind this game, as described in a previous article, is to create a Fall Guys: Ultimate Knockout tribute game with our own spin on it.

Since this game will be an online multiplayer game, each player needs to retain game-play information such as how many times they’ve won, what costumes they’ve unlocked, etc. This information would exist inside a user profile document.

In this tutorial, we’re going to see how to design a user profile store and then build a backend component using Node.js and MongoDB Realm for interacting with it.