coronavirus-dashboard-pipeline-etl
pgbouncer
| coronavirus-dashboard-pipeline-etl | pgbouncer | |
|---|---|---|
| 1 | 34 | |
| 5 | 2,656 | |
| - | 1.8% | |
| 7.2 | 8.7 | |
| 6 months ago | 2 days ago | |
| Python | C | |
| MIT License | 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.
coronavirus-dashboard-pipeline-etl
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Cascade of doom: JIT, and how a Postgres update led to 70% failure on a critical national service
use the cache pre-population solution implemented in our ETL
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.
What are some alternatives?
coronavirus-dashboard-summary - UK Coronavirus Dashboard - Summary pages
odyssey - Scalable PostgreSQL connection pooler
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
llvm-project - The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
pgcat - PostgreSQL pooler with sharding, load balancing and failover support. [Moved to: https://github.com/postgresml/pgcat]
coronavirus-dashboard-generic-apis - Coronavirus Dashboard (COVID-19) in the UK - Generic APIs
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
coronavirus-dashboard - Dashboard for tracking Coronavirus (COVID-19) across the UK
pgcat - PostgreSQL pooler with sharding, load balancing and failover support.
rds-auth-proxy - A "passwordless" login experience for your AWS RDS
citus - Distributed PostgreSQL as an extension