faunadb-js VS PostgreSQL

Fauna is another serverless database created by ex-Twitter engineers. It's kind of like MongoDB, but with native JOIN operations, many document databases miss. They have their own language, FQL, and also a GraphQL API. Here's a quick overview of their free tier:

Fauna[0] which if I recall correctly, also upends Cap Theorum. They implemented Calvin[1] which differs from Spanner

[0]: https://fauna.com/

[1]: https://fauna.com/blog/distributed-consistency-at-scale-span...

NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and Cassandra.

To create a Faunadb account you need to head over to the Fauna website. Click on Start for free then select Github as your auth provider, and authorize Faunadb from GitHub. If everything went well, your account should successfully be created for you and you should be redirected to your Faunadb dashboard.

I am using Fauna

Fauna

If you are exploring Amazon DynamoDB alternatives that are NoSQL and have better-querying capabilities, there are a few to choose from, but the one I will be covering here is Fauna. Fauna combines the querying capabilities of relational databases (SQL databases) with the flexibility of NoSQL databases.

Fauna – A serverless database with built in global replication and strong consistency.

Some of the largest websites, driven by the requirements of serving billions of users, have led to the maturation of new database architecture alternatives, which motivate modernizing applications to leverage cloud-native, serverless, highly-distributed database options. Fauna strengthens relational data consistency among these newer alternatives while leveraging a cloud-native, serverless, flexible document model that abstracts most operational complexities from application developers.

Multi-model: FaunaDB, MongoDB, Redis among others.

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.