sanity VS MongoDB

For Sanity users:

Sanity is a flexible and customizable headless content management system (CMS) designed to empower developers and content creators to build digital experiences. It has a free plan which includes a hosted, real-time content database which means you don’t have to go through the stress of looking for a backend service to deploy your backend Api.

Sanity.io - Platform for structured content with an open-source editing environment and a real-time hosted data store. Unlimited projects. Unlimited admin users, three non-admin users, two datasets, 500K API CDN requests, 10GB bandwidth, and 5GB assets included for free per project.

The world of web development is constantly evolving, with new tools and technologies emerging to optimize the content creation and management process. One such tool is the Sanity Presentation Tool, a powerful feature within the Sanity.io ecosystem designed to enhance the content editing experience. This tool bridges the gap between content management and frontend presentation, offering a seamless, real-time editing interface that is invaluable for content creators and developers alike.

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A headless one is responsible only for data management and providing an API for other applications to show this data. When talking about headless CMS, Strapi or Sanity comes to my mind first, but there are many more.

You could check out Storyblok, they have a nice free tier (most headless CMSes do) so you wouldn't have to pay for hosting. Some other good options are Prismic and Sanity Sanity.

I recently started a project using sanity as a headless cms, and it was pretty easy to set up. Looking at the pricing, you might even be able to stay on the free tier for this site.

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.