Stripe VS MongoDB

First let's introduce the tool: Sorbet is a gem developed by Stripe that aims to bring type notation syntax and type checking support for the Ruby ecosystem by utilizing the "Gradual typing" philosophy, it also provide type generation from YARD comments via the tapioca gem, allowing to grow alongside the already built Ruby codebase.

For me Stripe is the peak for a product/company website:

https://stripe.com/

I heard some people admire https://linear.app/ but I don't see the appeal myself

Majority of websites often fall into one of two categories:

1. Traditional off the shelf template

2. Look cool but fail when it comes to usability and robustness (those featured on awwwards)

You could have the best service in the world, but if you have a payment gateway that leaves people feeling uncomfortable, you'll lose them. Not only that, but you have PCI compliance you would need to deal with and a slew of other things that are handled for you with a payment vendor like Stripe, Square, or PayPal.

First you'll want to go to Stripe's website and setup an account. Then install Stripe with pip install stripe. In this example I'm using Flask for the backend and React for the frontend. The website is an e-commerce page for buying and selling skateboards. Now create some models for the product to sell and the receipts then run flask db init, flask db migrate, and flask db upgrade to create the database. My models look like so:

I've spent my fair share of time in Silicon Valley on some of the coolest startups in the tech scene. So, a lot of our inspiration comes from companies like Stripe (e.g. their landing page) and Linear (e.g. their gradient usage). And, the data display architecture you're referencing (down to the layout on shift on screen sizes) is almost a perfect clone of the NBA's. And there's definitely a team there that costs 7 figures who has researched every nook and cranny about making that the most optimal layout haha.

Look, absolutely millions of people are going to type credit card numbers into https://amazon.com and https://stripe.com and https://squareup.com/ this year and nobody will get their credentials stolen or their credit card compromised. I mean, far far fewer then from the waiter or checkout person taking a quick photo of your credit card while they run it through the Point of Sale device physically.

Toast uses SSL. So does Stripe (https://stripe.com/) and so does Square (https://squareup.com/us/en/payments). Everybody, without fail now uses HTTPS (SSL), they really do. That ship sailed. If you use the Chrome web browser, anything not serving up puppy pictures over HTTPS says "Not Secure" for the last HALF DECADE. If you google "PCI compliance" it's literally THE LAW that it is required for handling credit cards. Anybody not using HTTPS will get fined, and probably go to jail. The embarrassment of the programmers getting caught not using HTTPS would be amazing, like they would have trouble ever getting another job programming computers.

Stripe

I was developing a backend that integrates Stripe to manage customers and to process subscriptions. In one use case, it should search for user input in the metadata of Stripe subscriptions. When I looked up the documentation about how to use the search functionality I came across the Search Query Language. It looked like users could easily inject their own additional query clauses. After a simple check: Yes, e.g. for the user input "124' OR status:'active" all active subscriptions are returned as well.

Stripe is a complete payments platform that offer a developer-friendly way to accept payments online and in mobile apps. To learn more about Stripe, visit their website here.

MongoDB — a database service

MongoDB is an open source NoSQL Document database which horizontally scales utilizing clustered servers in replica-sets. A great option for testing and performing local development with MongoDB is using Docker and Docker Compose. The following docker compose spec will create a local docker container running MongoDB with the data persisted to a docker volume.

MongoDB (Mongoose)

Databases Backend developers use databases like MySQL, PostgreSQL, MongoDB (NoSQL), or Redis (an in-memory database) to store and manage data. It is important for persistent data storage and retrieval in web applications.

MongoDB{:target="_blank"} is a document-oriented database with high scalability and flexibility for handling unstructured or semi-structured data. It offers rich querying capabilities, indexing options, and support for distributed data storage with a technique called “sharding”.

NoSQL databases are non-relational databases with flexible schema designed for high performance at a massive scale. Unlike traditional relational databases, which use tables and predefined schemas, NoSQL databases use a variety of data models. There are 4 main types of NoSQL databases - document, graph, key-value, and column-oriented databases. NoSQL databases generally are well-suited for unstructured data, large-scale applications, and agile development processes. The most popular examples of NoSQL databases are MongoDB (document), Memgraph (graph), Redis (key-value store) and Apache HBase (column-oriented).

Our example application will be based on the ME*N stack where M is a MongoDB (but it could be MySQL, or any other) database. E is for Express, which is a backend framework that sits on top of Node.JS. There are others but Express is extremely common and will meet our needs well. N is for the JavaScript runtime Node.js but Deno and Bun are possible alternatives. Finally the * is for the frontend framework such as Angular (MEAN), React (MERN) or Vue (MEVN), to name a few. However, in our example we will not be using a framework (to keep it agnostic and besides it is not that complicated), instead we will be using the native web technologies (HTML, CSS and JS).

MongoDB is a highly scalable document-type database. Its flexible schema approach allows developers to adapt and modify the data structure as needed, providing agility in application development.

MongoDB is an open-source, document-oriented database, meaning it stores data in a semi-structured format similar to JSON (JavaScript Object Notation), known as BSON (Binary JSON).