pg_squeeze
PostgreSQL
pg_squeeze | PostgreSQL | |
---|---|---|
2 | 412 | |
408 | 14,890 | |
2.5% | 3.0% | |
8.3 | 10.0 | |
2 months ago | 1 day ago | |
C | C | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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pg_squeeze
- Pg_squeeze: An extension to fix table bloat
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PlanetScale Is Now GA
> I am estimating that your database space isn't MySQL, which is just fine of course.
You are absolutely right :) My background is strongly on Postgres, you can see from my profile more information if you want to.
So yes, I apologize if some of my questions are not applying or become to obvious for cases that are MySQL-based. But for the most part, I believe principles of operation are the same.
> [other comments]
As mentioned, thank you very much for the detailed information. This completes the picture that I was looking for. I will definitely go in more detail for some of the links provided.
This principle of operation is not too different from something I proposed to a Postgres project some time ago (https://github.com/cybertec-postgresql/pg_squeeze/issues/18). This tool indeed is conceptually pretty similar. It's a shame that supporting schema changes is not part of their focus at this point. It wouldn't do throttling either, but it shouldn't be a difficult feature to add, I guess.
For other users here that may be interested in the Postgres world, there are two tools that perform similar operation (creating a shadow table and filling it in the background), but are both focused on rewriting the table to avoid bloat, rather than for doing a schema migration:
* pg_repack (https://reorg.github.io/pg_repack/): the most used one, relies on triggers
PostgreSQL
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Essential Tools & Technologies for New Developers
Every time I buy a new computer, the first thing I install is the servers for MySql and Postgres, the two most common databases. This way, I can start the databases with a simple command like this:
- OpenBSD 7.3 を 7.4 へ アップグレード
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What do you want to watch next? This is why I built GoodWatch.
Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance
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System Design: Databases and DBMS
PostgreSQL
- Presentación del Operador LMS Moodle
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Introducing LMS Moodle Operator
The LMS Moodle Operator serves as a meta-operator, orchestrating the deployment and management of Moodle instances in Kubernetes. It handles the entire stack required to run Moodle, including components like Postgres, Keydb, NFS-Ganesha, and Moodle itself. Each of these components has its own Kubernetes Operator, ensuring seamless integration and management.
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Integrate txtai with Postgres
Another key feature of txtai is being able to quickly move from prototyping to production. This article will demonstrate how txtai can integrate with Postgres, a powerful, production-ready and open source object-relational database system. After txtai persists content to Postgres, we'll show it can be directly queried with SQL from any Postgres client
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Understanding SQL vs. NoSQL Databases: A Beginner's Guide
SQL (Structured Query Language) databases are relational databases. They organize data into tables with rows and columns, and they use SQL for querying and managing data. Examples include MySQL, PostgreSQL, and SQLite.
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From zero to hero: using SQL databases in Node.js made easy
Node.js, MySQL and PostgreSQL servers installed on your machine
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I Deployed My Own Cute Lil’ Private Internet (a.k.a. VPC)
Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).
What are some alternatives?
gh-ost - GitHub's Online Schema-migration Tool for MySQL
psycopg2 - PostgreSQL database adapter for the Python programming language
vitess - Vitess is a database clustering system for horizontal scaling of MySQL.
ClickHouse - ClickHouse® is a free analytics DBMS for big data
cstore_fdw - Columnar storage extension for Postgres built as a foreign data wrapper. Check out https://github.com/citusdata/citus for a modernized columnar storage implementation built as a table access method.
phpMyAdmin - A web interface for MySQL and MariaDB
tengo - Go La Tengo: a MySQL automation library
Firebird - FB/Java plugin for Firebird
Adminer - Database management in a single PHP file
SQLAlchemy - The Database Toolkit for Python
MariaDB - MariaDB server is a community developed fork of MySQL server. Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry.
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.