OpenLayers3 VS MongoDB

You probably know this, but in Google Maps at least, you can use browser zoom (ctrl/cmd +/-) to change the size of labels without zooming into the actual map.

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Speaking of maps, I got to work a fun zoom project a few years ago: https://map.fieldmuseum.org/

We used https://openlayers.org/ and thought long and hard about how to best handle zooming and variable levels of information density & visual hierarchy. If you zoom all the way out, we just highlight where the building is relative to the surroundings. As you start to zoom in, we start to highlight major exhibitions and entrances. Then as you zoom in more, we start showing recommended paths, smaller exhibitions, etc. The label sizes try to scale up and down at each level, smoothly, in order to balance readability and density.

Eventually you can reach the max zoom level and the labels will just grow bigger and bigger, but the SVGs dynamically shrink so they remain pictograms and not just contextless-lines.

Then if you keep going, you eventually find microscopic easter eggs :)

The code is pretty jank (and abandoned), but it's FOSS vanilla JS/HTML/CSS, and the only dependency is on OpenLayers: https://github.com/arcataroger/openlayers_indoor_map

In order to display the GeoJSON features on a map, we will use OpenLayers, which is a very powerful open-source mapping library that is also very simple to use.

OpenLayers is available via the ol npm package, offering developers a powerful toolkit for creating sophisticated maps. Here is a JavaScript implementation that utilizes OpenLayers to showcase a map:

Official Website: https://openlayers.org/

For web maps I'd strongly recommend using OpenLayers. While it's less convenient to get started with compared to the alternatives it's also much more feature-complete and you'll likely hit a ceiling in terms of functionality much later than you would with the others.

MongoDB

First, visit MongoDB Atlas and create an account, or sign in if you already have one. This article will guide you through the process of creating a MongoDB account. You should be redirected to your dashboard once you have completed the process. Locate the Connect button and click it.

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.