tsParticles VS MongoDB

I wrote an article in 2020 for using Mocha/Chai in a TypeScript project, that I'm using in tsParticles (leave a star if you want 🌟, it's free 👀).

At first, I attempted to create my own particle effect, but I realized it's actually a lot harder than it seems. So I went with a third-party library that is made specially for particles. You can check out the repo https://github.com/matteobruni/tsparticles. They have lots of neat effects.

tsParticles - Easily create highly customizable particles, confetti, and fireworks animations and use them as animated backgrounds for your website. Ready-to-use components available for Reacts, Angular, Svelte, and Web Components.

I had a similar idea. Listen for a sequence of keys like "confetti" and then use https://particles.js.org/ to throw confetti all over the screen

You’re almost done! You just have to configure your particles/objects in order of animation, interaction, direction, opacity, etc. For this illustration, you’ll be using an already preset configuration from the tsparticles repository, but you can always tweak it to your own style or create one from scratch if you’d like.

And last but not least, the two websites (https://particles.js.org and https://confetti.js.org) have two dedicated repositories:

Are you thinking of this, or particles.js? particles.js has been used in Pterodactyl (and probably in other login pages), whereas tsParticles seems to be much more programmable.

You can still use a json config file even with a pure JS implementation from what I see here https://github.com/matteobruni/tsparticles

On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra.

I built each API with Node.js, Express, and Docker. Services connected to a NoSQL MongoDB database.

In edge computing, managing time series blob data efficiently is critical for performance-sensitive applications. This blog post will compare ReductStore, a specialized time series database for unstructured data, and MongoDB, a widely-used NoSQL database.

MongoDB to store our data as documents, close to JS objects

MongoDB: Known for its ease of development and strong community support, MongoDB is effective in scenarios where flexible schema and rapid iteration are more critical than strict ACID compliance.

MongoDB

Ensure you have MongoDB installed for data storage. You can download MongoDB Community Server from MongoDB's official website or use the cloud cluster.

We will be using MongoDB as a database on both the Auth microservice and notifications microservice, sign up for a MongoDB Atlas account here incase you donot have one and donot have its desktop application(mongodb campass) installed and would like to use mongodb atlas. This cloud-based database service offers a free tier and simplifies the process of managing MongoDB databases.

Head over to MongoDB and create an account or login to grab your connection string.

MongoDB, a document-oriented NoSQL database, will be our data powerhouse. We'll utilize the mongo-driver library to seamlessly connect our Golang application to MongoDB. This section will cover essential database interactions, including creating collections, storing metadata, and efficiently querying for image-related data. Understanding these fundamentals is crucial for building a robust image storage and retrieval system.