mason-registry VS PostgreSQL

Can you try to get it added to Mason so people don't have to try and do a custom install?

https://github.com/mason-org/mason-registry/

There was a bug in the new mason registry that I fixed this morning: https://github.com/mason-org/mason-registry/pull/1056

Hello! This is a PSA for people who use mason.nvim (tl;dr at the bottom). Going forward the core registry will be hosted as a collection of static, YAML-based, package definitions at https://github.com/mason-org/mason-registry, as opposed to bundled with the mason.nvim plugin itself as Lua modules. This decouples the infrastructure in such a way that the Lua plugin becomes a standalone client that can be hooked into more registries than just the core one, as well as more easily be subject to versioning (mason.nvim currently doesn't version itself due to the fact that packages are bundled with it, which complicates things). This decoupling also lowers the barrier of entry for additional maintainers who can solely focus on the registry, without having to learn the internals of the plugin (more info will come soon if you're interested in possibly helping maintain the core registry).

Going forward the core mason.nvim package registry will be hosted as a collection of static, YAML-based, package definitions at https://github.com/mason-org/mason-registry, as opposed to bundled with the mason.nvim plugin itself as Lua modules. This will be a fully seamless migration so you shouldn't notice anything and there is no action required. Refer to the full announcement post for more information.

Every time I buy a new computer, the first thing I install is the servers for MySql and Postgres, the two most common databases. This way, I can start the databases with a simple command like this:

Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance

PostgreSQL

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).