pgbouncer
PostgreSQL
pgbouncer | PostgreSQL | |
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34 | 412 | |
2,692 | 14,890 | |
3.1% | 3.0% | |
8.7 | 10.0 | |
5 days ago | 1 day ago | |
C | C | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pgbouncer
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MongoDB and Load Balancer Support
Thanks to MongoDB drivers all consistently providing connection monitoring and pooling functionality, external connection pooling solutions aren't required (ex: Pgpool, PgBouncer). This allows applications built using MongoDB drivers to be resilient and scalable out of the box, but based on what we understand regarding the number of connections applications establish to MongoDB clusters it stands to reason that at a certain point as our application deployments increase, so will our connections.
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Minha jornada de otimização de uma aplicação django
Pgbouncer - resolvia o problema do limite de conexões no postgres. Mas a API “saudável” manteve o número de conexões baixo o suficiente.
- PgBouncer 1.21.0 – "The one with prepared statements"
- Pgbouncer adds support for prepared statements
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PgBouncer is useful, important, and fraught with peril
Pgbouncer maintainer here. Overall I think this is a great description of the tradeoffs that PgBouncer brings and how to work around/manage them. I'm actively working on fixing quite a few of the issues in this blog though
1. Named protocol-level prepared statements in transaction mode has a PR that's pretty close to being merged: https://github.com/pgbouncer/pgbouncer/pull/845
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Supavisor: Scaling Postgres to 1 Million Connections
A common solution is connection pooling. Supabase currently offers pgbouncer which is single-threaded, making it difficult to scale. We've seen some novel ways to scale pgbouncer, but we have a few other goals in mind for our platform.
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Citus 12: Schema-based sharding for PostgreSQL
Great observation! :)
We worked upstream to have `search_path` properly handled (tracked per client) by pgbouncer.
https://github.com/pgbouncer/pgbouncer/commit/8c18fc4d213ad4...
Check config.md in that commit for a verbose, humanized description.
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?
odyssey - Scalable PostgreSQL connection pooler
psycopg2 - PostgreSQL database adapter for the Python programming language
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
ClickHouse - ClickHouse® is a free analytics DBMS for big data
pgcat - PostgreSQL pooler with sharding, load balancing and failover support. [Moved to: https://github.com/postgresml/pgcat]
phpMyAdmin - A web interface for MySQL and MariaDB
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
Firebird - FB/Java plugin for Firebird
pgcat - PostgreSQL pooler with sharding, load balancing and failover support.
Adminer - Database management in a single PHP file
rds-auth-proxy - A "passwordless" login experience for your AWS RDS
SQLAlchemy - The Database Toolkit for Python