lzsa VS PostgreSQL

True.

If you're on your way down this rabbit hole, there's a bunch of old-machine-specific compression algorithms, developed by the emulator community, e.g. LZSA: https://github.com/emmanuel-marty/lzsa

There's quite a lot of retro modern LZ activity too! LZ turns out to be amazing on old machines, often only several times slower than a block copy. Optimal compressors and control over the algorithm have led to some very tight demos.

https://www.brutaldeluxe.fr/products/crossdevtools/lz4/index... LZ4 Data Compression - a rather long and in-depth article looking at LZ4 on the 65816 for the Apple IIgs

https://github.com/emmanuel-marty/lzsa - LZSA - a LZ4-like modern LZ that's more efficient both in speed and compression to LZ4 (at least on the 8 bitters it targets).

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).