pgbouncer
slonik
pgbouncer | slonik | |
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34 | 71 | |
2,692 | 4,398 | |
3.1% | - | |
8.7 | 9.3 | |
5 days ago | 7 days ago | |
C | TypeScript | |
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.
slonik
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Sneakiest development trap: making easy easier...
And sometimes invest instead in learning a technology rather than hide it: for example slonik encourages you to write normal SQL queries by making SQL templating easier and safer. In turn, your IDE would be able to understand those queries and give you support based on the database schemas you actually have.
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Drizzle is just as unready for prime-time as Prisma, what else is there?
I'd push you to consider using postgres, slonik or similar for database queries. With these libraries, you just write SQL, but they perform input sanitization for you. So you can safely write:
- Slonik: PostgreSQL client for Node.js with runtime validation
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PostgresJs: The Fastest full featured PostgreSQL client for Node.js and Deno
You can already use postgres with Slonik.
https://github.com/gajus/slonik#user-content-slonik-how-are-...
It is not going to be the default because it is way slower.
https://github.com/gajus/slonik/actions/runs/6616647651
Test node_version:18 test_only:postgres-integration is taking 3 minutes.
Test node_version:18 test_only:pg-integration is taking 38 seconds.
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Integrating Slonik with Express.js
For those uninitiated, Slonik is a battle-tested SQL query building and execution library for Node.js. Its primary goal is to allow you to write and compose SQL queries in a safe and convenient way. Now, let's see how it pairs with Express.js.
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Which Postgres client are you using?
I am the maintainer of Slonik and I am trying to understand what portion of this sub-users are using Slonik vs other libraries, and if they are using anything else – what are their reasons for it.
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JEP Draft: String Templates (Final)
It's nice that they implemented string templates essentially exactly the same way Javascript template literals and tag functions work. They even give an example of using it to create a prepared statement (e.g. DB."SELECT * FROM foo WHERE bar = \{inputParam}") which is exactly what many NodeJS libraries due, e.g. Slonik https://github.com/gajus/slonik, like sql`SELECT * FROM foo WHERE bar = ${inputParam}`;
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We use TypeScript not based on preference, but because we want to make money
I've found libraries like Zod useful when interacting with external data sources like a database. Slonik[1] uses Zod to define the types expected from a SQL query and then performs runtime validation on the data to ensure that the query is yielding the expected type.
I don't think it's necessary to use Zod/runtime validation everywhere, but it's a nice tool to have on hand.
[1]https://github.com/gajus/slonik
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Is ORM still an anti-pattern?
Demonstrate how easily and accidentally one can make an SQL injection with these:
https://github.com/porsager/postgres
https://github.com/gajus/slonik
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The Epic Stack by Kent C. Dodds
Have you tried Slonik (https://github.com/gajus/slonik)? It won't generate types from queries automatically, but it encourages writing SQL vs. a query builder and allows type annotations of queries with Zod. Query results are validated at runtime to ensure the queries are typed correctly.
What are some alternatives?
odyssey - Scalable PostgreSQL connection pooler
Knex - A query builder for PostgreSQL, MySQL, CockroachDB, SQL Server, SQLite3 and Oracle, designed to be flexible, portable, and fun to use.
asyncpg - A fast PostgreSQL Database Client Library for Python/asyncio.
TypeORM - ORM for TypeScript and JavaScript. Supports MySQL, PostgreSQL, MariaDB, SQLite, MS SQL Server, Oracle, SAP Hana, WebSQL databases. Works in NodeJS, Browser, Ionic, Cordova and Electron platforms.
pgcat - PostgreSQL pooler with sharding, load balancing and failover support. [Moved to: https://github.com/postgresml/pgcat]
Prisma - Next-generation ORM for Node.js & TypeScript | PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, MongoDB and CockroachDB
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
Sequelize - Feature-rich ORM for modern Node.js and TypeScript, it supports PostgreSQL (with JSON and JSONB support), MySQL, MariaDB, SQLite, MS SQL Server, Snowflake, Oracle DB (v6), DB2 and DB2 for IBM i.
pgcat - PostgreSQL pooler with sharding, load balancing and failover support.
pgtyped - pgTyped - Typesafe SQL in TypeScript
rds-auth-proxy - A "passwordless" login experience for your AWS RDS
pg-promise - PostgreSQL interface for Node.js