What is PostgreSQL?
Who uses PostgreSQL?
Here are some stack decisions, common use cases and reviews by companies and developers who chose PostgreSQL in their tech stack.
PostgreSQL is responsible for nearly all data storage, validation and integrity. We leverage constraints, functions and custom extensions to ensure we have only one source of truth for our data access rules and that those rules live as close to the data as possible. Call us crazy, but ORMs only lead to ruin and despair. PostgreSQL
We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).
We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .
Read the blog post to go more in depth.
We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQL 's extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.
Investigating Tortoise ORM and GINO ORM...
I need to introduce some async ORM with the current stack: Tornado with asyncio loop, AIOHTTP , with PostgreSQL and MSSQL . This project revolves heavily around realtime and due to the realtime requirements, blocking during database access is not acceptable.
Considering that these ORMs are both young projects, I wondered if anybody had some experience with similar stack and these async ORMs?
At IT Minds we create customized internal or #B2B web and mobile apps. I have a go to stack that I pitch to our customers consisting of 3 core areas. 1) A data core #backend . 2) A micro #serverless #backend. 3) A user client #frontend.
For the Data Core I create a backend using TypeScript Node.js and with TypeORM connecting to a PostgreSQL Exposing an action based api with Apollo GraphQL
For the micro serverless backend, which purpose is verification for authentication, autorization, logins and the likes. It is created with Next.js api pages. Using MongoDB to store essential information, caching etc.
Finally the frontend is built with React using Next.js , TypeScript and @Apollo. We create the frontend as a PWA and have a AMP landing page by default.
I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.
We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec .
Our main database is PostgreSQL , but we also use MongoDB to store some type of data. We started to use Redis for cache and other time sensitive operations.
We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.