PostgreSQL VS psycopg2

While both Postgres and ClickHouse serve different purposes, the key distinction lies in how they handle replication and sharding. Postgres is primarily designed for transactional workloads (OLTP), where data consistency and durability are prioritized. On the other hand, ClickHouse is tailored for analytical workloads (OLAP), and optimized for high-speed querying and large-scale data analysis.

For your information, the tuplesort.c module flags when the Sort algorithm will use disk by setting the state to SORTEDONTAPE at this line. Disk interactions is handled by the logtape.c module.

This error happens when using a relational database, like PostgreSQL (one of the most popular, and advanced open-source SQL databases on the market).

This tutorial is going to use Postgres for its database because it is well battle-tested, but you're going to use the Prisma ORM to abstract away the database layer. This gives you the flexibility to use a variety of databases, and simplifies the API that you use to interact with it.

Yes, it's a balancing act. I think it's better to have safer defaults here, not prioritizing extra performance. People who are concerned with performance to the degree where checksums would matter need to consult configuration anyway (in many aspects, not only this one) and can disable this specific thing easily.

For the reference, change is in https://github.com/postgres/postgres/commit/04bec894a04c (so should land in PostgreSQL 18 in a year, unless it will get reverted for some reason).

PostgreSQL, commonly referred to as Postgres, is a powerful, open-source relational database management system (RDBMS) known for its robustness, extensibility, and standards compliance. It was introduced in 1986 by Michael Stonebraker and his team at the University of California, Berkeley, as part of the POSTGRES project, which aimed to address some of the limitations of existing database systems at the time.

PostgreSQL: An open-source object-relational database management system, used early on by Uber.

PostgreSQL

Link: https://www.postgresql.org/

When building web applications, authentication is almost always a core requirement. I needed something simple and secure that would let me get started quickly on new projects without over-complicating the setup. My goal was to have a solution that's easy to implement, handles email verification out of the box, and just works. In this post, I'm sharing how to build a straightforward magic link authentication system using Next.js, Auth.js, Prisma, PostgreSQL, and Resend. It's a powerful yet simple solution that accomplishes exactly what I needed, and I hope it'll be useful for your projects too.

# Palindrome project Project used to explain my view on a django project architecture, explained on my [series of posts](https://dev.to/pcampos119104/django-project-setup-part-1-2e7a) ## Tools, libs, etc. Some time related files. Versions on Poetry. - [Python](https://www.python.org/) Programming languange - [django-environ](https://django-environ.readthedocs.io) Manage .envs in Django - [Poetry](https://python-poetry.org/) Python packaging and dependency management - poetry.lock - pyproject.toml - [Django](https://www.djangoproject.com/) Web framework written in Python - [Docker](https://www.docker.com/) Manage containers for dev environment - compose.yaml - compose/dev/Dockerfile - compose/dev/start - .env - [Just](https://just.systems/) encapsulate commands for easier use - justfile - [psycopg](https://www.psycopg.org/) Python adapter for Postgres # <-- new line ## Dev environment setup 1. Install Just, Docker and Poetry(opcional). 2. Copie .env.example to .env, no need for edtion. 3. `$ just build` ## Run the server for development 1. Certified that docker is up and running 2. `$ just runserver` You can access on http://0.0.0.0:8000/

You can practice both by using https://www.psycopg.org from your Python code to communicate with your database. When I wanted to practice some SQL, that's what I did (we use psycopg at work, so that's what I practiced with, making a dream journal thingy for myself that was better than just noting stuff in a notepad because I could then look up e.g. what other stuff was correlated with Y, how many times I dreamed of X, etc. etc.)

But seems like it should work with Django 3, which you have specified https://github.com/psycopg/psycopg2/issues/1293

If you're using Postgres for your SQL, look at the "copy' method of the psycopg module (see https://www.psycopg.org/articles/2020/11/15/psycopg3-copy/) . It's much faster than INSERTs in my experience (YMMV).

Back when I used Psycopg2, there was no -binary package, so you'd get libpq set up similarly to pg-native. Docs say:

> The binary package is a practical choice for development and testing but in production it is advised to use the package built from sources.

Relevant GitHub discussion: https://github.com/psycopg/psycopg2/issues/674

I dunno, this seems worse to me.

Just go to the more easily readable docs here. I’m sorry, but the linked article is terrible.

psycopg2-binary. See https://github.com/psycopg/psycopg2/issues/1286.

psycopg2-binary, PostgreSQL Database adapter for python.

... # psycopg2==2.9.3 # https://github.com/psycopg/psycopg2 ...

I sometimes do this in testing. For example, consider the library used to communicate with a Postgres database, psycopg.