gatsby-starter-medusa VS PostgreSQL

gatsby new medusa-gatsby https://github.com/medusajs/gatsby-starter-medusa

This tutorial uses the Gatsby starter to test the wishlist functionality added to the Medusa server. However, you can still follow along using a different storefront framework.

Last month, our team at Medusa built a new advanced Next.js storefront that can be used with a Medusa server. If interested in other Medusa starters, feel free to check out Medusa.Express or our Gatsby starter.

In this tutorial, you’ll learn how to add live-chat functionality to your ecommerce store using Medusa, Tidio live chat, and Gatsby Storefront.

Medusa provides two starter storefronts, one built using Next.js and one using Gatsby. You can also build your own storefront by interacting with the REST APIs.

The difficult part is for the modification of store frontend. I use Medusa Gatsby Starter to my store frontend. However, there are many incompatible with my above modification of backend.

git clone https://github.com/medusajs/gatsby-starter-medusa.git storefront

This creates a Gatsby website using the already-existing Medusa Gatsby starter.

It gives you full flexibility to build any type of frontend(s) you may prefer - Medusa has starters in Next.js or Gatsby to set up a high-performing storefront out-of-the-box so you have a good starting point before starting to customize it to your needs. You can check out a demo of the starer here.

GatsbyJS (much more feature-rich V2 coming soon)

The LMS Moodle Operator serves as a meta-operator, orchestrating the deployment and management of Moodle instances in Kubernetes. It handles the entire stack required to run Moodle, including components like Postgres, Keydb, NFS-Ganesha, and Moodle itself. Each of these components has its own Kubernetes Operator, ensuring seamless integration and management.

Another key feature of txtai is being able to quickly move from prototyping to production. This article will demonstrate how txtai can integrate with Postgres, a powerful, production-ready and open source object-relational database system. After txtai persists content to Postgres, we'll show it can be directly queried with SQL from any Postgres client

SQL (Structured Query Language) databases are relational databases. They organize data into tables with rows and columns, and they use SQL for querying and managing data. Examples include MySQL, PostgreSQL, and SQLite.

Node.js, MySQL and PostgreSQL servers installed on your machine

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

I've used MySQL for years. But recently, I found myself working PostgreSQL and simple things like dumping and restoring a database are different enough that I decided to document the process. It's straightforward enough once I knew how.

A running Rails application needs a database to connect to. You may already have your database of choice installed, but if not, I recommend PostgreSQL, or Postgres for short. On a Mac, probably the easiest way to install it is with Posrgres.app. Another option, the one I prefer, is to use Homebrew. With Homebrew installed, this command will install PostgreSQL version 16 along with libpq:

PostgreSQL

PostgreSQL: Offers a robust feature set and strong compliance with SQL standards, making it suitable for a wide range of applications, from simple to complex, particularly where data integrity and extensibility are key.