#PYTHON POSTGRESQL VS MYSQL HOW TO#
#PYTHON POSTGRESQL VS MYSQL CODE#

When it comes to deploying REST servers on GCP, there are two main options to choose from: Cloud Run and App Engine.Ĭloud Run is a fully-managed, container-based platform that allows you to run stateless HTTP containers in a serverless environment. By separating these responsibilities, your app can be more efficient and easier to maintain over time. The database is designed to store and maintain data integrity, while the REST server is responsible for handling individual, independent requests that operate on the data stored in the database. While it's essential for your app to keep track of user data, it's important to remember that this responsibility falls on the database. Since each request can be handled by any instance of the server, failures or crashes can be quickly detected and handled by spinning up new instances. Stateless servers also offer other benefits, such as improved reliability and fault tolerance. This is in contrast to stateful servers, which need to keep track of session data and ensure that each request is handled by the same server instance. This makes it easier to scale and deploy, since any instance of the server can handle any incoming request. When a server is stateless, it means that it doesn't store any session data or state information between requests.

Why Stateless REST Servers are Ideal for Cloud Deploymentsīefore diving into the details of building a REST server with GCP, let's first take a step back and consider why stateless servers are ideal for cloud deployments.

#PYTHON POSTGRESQL VS MYSQL CODE#

At the end of the blog post, I’ll also include all the source code to help you follow along the explanations given in the post itself.

#PYTHON POSTGRESQL VS MYSQL HOW TO#

In this blog post, we'll explore how to build a REST server using FastAPI, PostgreSQL, and GCP, and deploy it to a stateless environment like GCP Cloud Run. Your initial investment is also significantly lower, as you’ll just have to pay for what you consume, instead of buying a whole server up-front. With a cloud provider like GCP, you won’t have to worry about keeping your servers up 100% of the time and making sure they are available, also with high traffic loads. One particularly appealing option is to use cloud providers like Google Cloud Platform (GCP), which offer scalable, stateless services like Cloud Run and App Engine. When it comes to deploying REST servers, there are many options to choose from. It's worth noting that the guide can be easily adapted for other databases like MySQL or MongoDB with minimal modifications. In this blog post, we will explore how to connect our FastAPI server with a PostgreSQL database. Additionally, PostgreSQL's compatibility with multiple platforms ensures flexibility in deployment. PostgreSQL's reputation for reliability and stability further solidifies its position as a trusted solution. Its extensive community and ecosystem provide invaluable support, making it easier to solve problems. Among the various database options available, PostgreSQL stands out as a popular choice for developers.

Take into account that good documentation and a broad community can save you tons of time when developing your backend.īuilding a web application involves more than just a web server it requires a reliable and efficient database to store and manage the application's stateful data. Apart from its performance, powered by the usage of the asyncio library, I was convinced by the core integration of type annotations and the well-built documentation. When I was building Ballistic, I chose for FastAPI as the web framework for my backend API in Python, since it had gained significant popularity in the Python community in a very short amount of time. One popular approach for building backends is by using RESTful APIs, which enable clients to communicate with servers using HTTP requests.

In the world of web development, a robust backend is crucial for delivering a high-quality user experience.

Python postgresql vs mysql