MySQL VS PostgreSQL

You can find detailed installation instructions in the docs. We will choose the Docker installation and use a MySQL database as a persistent data store.

DbSchema is not a database itself. It’s a visual tool that connects to your MySQL or MongoDB server and works directly with your database. Once connected, it shows you the real structure of your data - the tables or collections, the columns or fields, and even the relationships between them. You can explore the data, edit the schema, and understand your database more clearly, all in one place.

MySQL MySQL natively supports partitioning, but sharding needs add-ons like Vitess to run platforms like YouTube.

Open source software is built on the democratic idea that everyone should be able to inspect and contribute to the source code. Major projects like Linux, WordPress, and the Apache HTTP Server have shown how collaborative efforts can produce robust, scalable solutions. Indie hackers, often working with limited budgets, gain access to highly dependable tools such as Python and MySQL, which were originally developed and maintained by global communities.

Hey everyone! I recently got fed up with waiting minutes for simple analytics queries to finish, so I threw together a little demo to see how SingleStore, MySQL, and PostgreSQL stack up against each other on a 110 million‑row banking transactions dataset.

Traditional databases — PostgreSQL, MySQL, etc. — store their data in proprietary formats. That format is optimized for that engine and can’t be directly accessed by anything else. Even if something like Trino can connect to Postgres, it’s still running queries through Postgres itself, not reading its storage directly. You’re just a client.

Propagating changes from operational databases (Postgres, MySQL, etc.) via CDC into Iceberg requires careful handling. Since Iceberg tables typically lack primary key enforcement at the storage layer, updates and deletes must often be implemented via equality deletes: deleting the old row version and inserting the new one. A streaming ingest engine must reliably:

MySQL X protocol solves some of these

* Notifies a client when a session variable has changed. Though I haven't used it so possibly not implemented.

https://github.com/mysql/mysql-server/blob/trunk/plugin/x/pr...

* Allows sending parameterised SQL and a collection of values together without preparing.

https://github.com/mysql/mysql-server/blob/trunk/plugin/x/pr...

mysql

Additionally, Beego includes a robust Object-Relational Mapper (ORM) that simplifies database interactions. Instead of writing complex SQL queries, developers can manipulate data using Go objects while the ORM handles the translation to and from the database. It supports popular database systems such as MySQL, PostgreSQL, and SQLite.

PostgreSQL as database

> As introduced in the previous chapters, all identifers are hashed, thus we can also hash the known keywords at startup and make comparing them very fast.

One trick that postgres uses [1][2] is perfect hashing [3]. Since you know in advance what your keywords are, you can design such hashing functions that for each w(i) in list of i keywords W, h(w(i)) = i. It essentially means no collisions and it's O(i) for the memory requirement.

[1] https://github.com/postgres/postgres/blob/master/src/tools/P...

[2] https://github.com/postgres/postgres/blob/master/src/tools/g...

[3] https://en.wikipedia.org/wiki/Perfect_hash_function

Understanding a database starts with understanding its structure. For PostgreSQL users, one of the most effective ways to visualize and manage your schema is by using an Entity-Relationship Diagram (ERD). Either if you're working with a large legacy database or starting something new, an ER diagram shows how your tables are connected and how your data is organized.

PostgreSQL supports two ways to store structured data in a column: JSON and JSONB.

On PostgreSQL create a database. In this tutorial, we will name it imageboard.

PostgreSQL and Partitioning PostgreSQL versions 10 and after have advanced native partitioning, making it ideal for time-series data, logs, and historical datasets. For example, a fintech app partitioning by month to improve query speeds.

The following commit was added to the PostgreSQL master branch (REL_18_BETA1):

We got a database for free when we provisioned last time, but if we want to target another database, we can surely do that as the service at this time of writing supports transforming to flavors of Postgres as well.  For this we will outline how to wrangle an external database, via Amazon RDS, and connect it to the service.

This quick start guide gets you up and running with Quarkus on macOS, including necessary tools. You will build a basic database application using Quarkus, Java 17, PostgreSQL, and Hibernate ORM Panache. While Hibernate ORM is the standard, powerful Jakarta Persistence implementation capable of complex mappings, it doesn't always make the most common tasks trivial. Hibernate ORM with Panache is Quarkus's solution to this, focusing specifically on making your data entities and repositories simple, straightforward, and fun to write by reducing boilerplate code for common persistence operations.