mongodb-queue alternatives and similar packages
Based on the "Database" category.
Alternatively, view mongodb-queue alternatives based on common mentions on social networks and blogs.
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erd
Translates a plain text description of a relational database schema to a graphical entity-relationship diagram. -
HDBC-session
This repository includes a joined query generator based on typefull relational algebra, and mapping tools between SQL values list and Haskell record type. -
groundhog
This library maps datatypes to a relational model, in a way similar to what ORM libraries do in OOP. See the tutorial https://www.schoolofhaskell.com/user/lykahb/groundhog for introduction -
mysql-simple
A mid-level client library for the MySQL database, intended to be fast and easy to use. -
dbmigrations
DISCONTINUED. A library for the creation, management, and installation of schema updates for relational databases. -
ampersand
This repository contains the source code of the Ampersand compiler. For developing in VS-code, it contains a devcontainer. It contains a Dockerfile for generating a docker image. A commit on the main branch sets of the build street, which creates a new image in the ampersand repository in docker hub. -
hsparql
hsparql includes a DSL to easily create queries, as well as methods to submit those queries to a SPARQL server, returning the results as simple Haskell data structures.
InfluxDB high-performance time series database

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README
haskell-mongodb-queue
inspiration from MongoMQ
Initial introductory blog post
See the haddocks.
A simple messaging queue using MongoDB. This trades having a good queue for ease of deployment. This is designed to be much worse at scale than real queueing infrastructure. However, it is very simple to start using if you are already running MongoDB. You could probably fork this code to make it work with a different database that you are already using. . There are 2 options for receiving a message: polling or tailable cursors. Polling is obviously inefficient, but it works against an index on a capped collection, so it should still be fairly efficient, and as fast as the polling interval you set. Tailable cursors respond very quickly and don't re-query the database. However, there is an outstanding bug that they use up CPU on the database when the system is idle, particularly as more tailable cursors are added. The idle CPU usage will become worse as you scale out to multiple worker processes.