async vs p-queue vs queue vs bull vs agenda vs bee-queue vs kue
Job and Task Queues in Node.js
asyncp-queuequeuebullagendabee-queuekueSimilar Packages:
Job and Task Queues in Node.js

Job and task queues in Node.js are essential for managing background tasks, handling asynchronous operations, and improving the scalability of applications. These queues allow developers to offload time-consuming tasks, such as sending emails, processing images, or performing complex calculations, to be executed separately from the main application flow. This helps in optimizing resource usage, reducing response times, and ensuring a smoother user experience. Libraries like agenda, async, bee-queue, bull, kue, p-queue, and queue provide various features and implementations for managing these tasks efficiently, each with its own strengths and use cases.

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async71,752,80328,220808 kB22a year agoMIT
p-queue11,976,1594,01972.4 kB614 days agoMIT
queue6,371,63577519.6 kB203 years agoMIT
bull1,078,76316,177309 kB148a year agoMIT
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bee-queue34,4023,995106 kB442 years agoMIT
kue20,7189,459-2888 years agoMIT
Feature Comparison: async vs p-queue vs queue vs bull vs agenda vs bee-queue vs kue

Storage Backend

  • async:

    async does not provide a storage backend, as it is a utility library for managing asynchronous operations in memory. It is designed for tasks that can be completed within the application's runtime without the need for persistence.

  • p-queue:

    p-queue does not use an external storage backend, as it manages tasks in memory. It is designed for lightweight applications that require concurrency control without the overhead of persistent storage.

  • queue:

    queue is an in-memory queue that does not rely on external storage. It is suitable for applications that need simple, fast queueing without the complexity of managing persistent data.

  • bull:

    bull also uses Redis as its storage backend, offering robust support for job persistence, retries, and delayed jobs. It is designed for applications that need reliable and scalable queue management.

  • agenda:

    agenda uses MongoDB as its storage backend, allowing for persistent job storage and retrieval. This makes it suitable for applications that require durability and the ability to recover jobs after a restart.

  • bee-queue:

    bee-queue uses Redis as its storage backend, providing fast and efficient job storage with low latency. It is optimized for high-throughput applications that require quick access to job data.

  • kue:

    kue uses Redis for storing job data, including priorities, statuses, and progress. It provides a simple and efficient way to manage jobs with support for persistence and recovery.

Concurrency Control

  • async:

    async provides various methods for controlling concurrency, such as async.parallelLimit and async.queue, which allow developers to limit the number of concurrent tasks. This flexibility makes it easy to manage resource usage while executing asynchronous operations.

  • p-queue:

    p-queue is designed for concurrency control, allowing developers to set the maximum number of concurrent tasks. It also supports rate limiting, making it ideal for scenarios where tasks need to be throttled.

  • queue:

    queue provides basic concurrency control by allowing multiple tasks to be processed simultaneously. The concurrency level can be configured to suit the application's requirements.

  • bull:

    bull offers advanced concurrency control features, including the ability to set the number of concurrent processors for a queue. It also supports job prioritization and rate limiting, making it a versatile choice for managing complex workloads.

  • agenda:

    agenda allows for concurrency control by specifying the number of jobs that can run simultaneously. This helps prevent resource exhaustion and ensures that tasks are processed efficiently.

  • bee-queue:

    bee-queue supports concurrency by allowing multiple workers to process jobs simultaneously. The concurrency level can be configured to optimize performance based on the application's needs.

  • kue:

    kue allows for concurrency by enabling multiple workers to process jobs in parallel. The concurrency level can be adjusted to balance performance and resource usage.

Job Scheduling

  • async:

    async does not provide built-in job scheduling capabilities, as it focuses on managing asynchronous operations. Scheduling would need to be implemented separately using timers or other mechanisms.

  • p-queue:

    p-queue does not provide job scheduling features, as it is focused on managing the execution of tasks based on concurrency and rate limits. Scheduling would need to be handled separately.

  • queue:

    queue is a simple FIFO queue that does not include built-in scheduling features. Tasks are processed in the order they are added, without support for delays or recurring execution.

  • bull:

    bull offers robust job scheduling features, including support for delayed and recurring jobs. It is well-suited for applications that need advanced scheduling capabilities with fine-grained control.

  • agenda:

    agenda excels in job scheduling, particularly for recurring tasks. It allows developers to schedule jobs at specific intervals, making it ideal for applications that require automated, time-based task execution.

  • bee-queue:

    bee-queue supports delayed jobs, allowing tasks to be scheduled for execution after a specified delay. However, it does not have built-in support for recurring jobs.

  • kue:

    kue supports delayed jobs, allowing tasks to be scheduled for future execution. However, it lacks native support for recurring jobs, which would need to be implemented manually.

Monitoring and UI

  • async:

    async does not provide any monitoring or UI features, as it is a utility library for managing asynchronous tasks. Monitoring would need to be implemented separately.

  • p-queue:

    p-queue does not offer any monitoring or UI features, as it is a lightweight library focused on concurrency control. Monitoring would need to be implemented separately.

  • queue:

    queue does not include any built-in monitoring or UI features. It is a simple queue implementation that relies on external tools for tracking and visualization.

  • bull:

    bull includes a popular UI called Bull Board for monitoring queues, jobs, and workers. This makes it easy to track job status, view metrics, and manage queues in real-time.

  • agenda:

    agenda does not include a built-in UI for monitoring jobs, but there are third-party tools and integrations available. Developers can also create custom dashboards using the MongoDB data.

  • bee-queue:

    bee-queue does not have a built-in UI, but it provides APIs for monitoring job status and progress. Developers can create custom dashboards or use third-party tools for visualization.

  • kue:

    kue comes with a built-in web UI for monitoring jobs, viewing their statuses, and managing the queue. This feature makes it easy to track job progress and identify issues.

Ease of Use: Code Examples

  • async:

    async offers a wide range of functions for managing asynchronous workflows, including queues. Its documentation is comprehensive, making it easy for developers to understand and implement various patterns.

  • p-queue:

    p-queue is designed for simplicity, with a clear API for managing concurrency and rate limits. Its promise-based design makes it easy to integrate into modern JavaScript applications.

  • queue:

    queue offers a straightforward API for adding and processing tasks. Its simplicity makes it easy to implement, but it lacks advanced features found in other libraries.

  • bull:

    bull provides a rich API with features like job prioritization, retries, and rate limiting. Its documentation is thorough, and the inclusion of Bull Board makes it user-friendly for managing queues.

  • agenda:

    agenda provides a simple API for defining and scheduling jobs. Its integration with MongoDB makes it easy to manage job data, and its support for recurring tasks is straightforward to use.

  • bee-queue:

    bee-queue has a simple API for creating and processing jobs. Its focus on performance is reflected in its design, but it remains easy to use for developers familiar with Redis.

  • kue:

    kue has an intuitive API for creating jobs and setting priorities. Its built-in UI enhances usability by providing a visual interface for monitoring job status.

How to Choose: async vs p-queue vs queue vs bull vs agenda vs bee-queue vs kue
  • async:

    Choose async if you need a comprehensive utility library for managing asynchronous operations, including task queues, parallel execution, and flow control. It is suitable for projects that require fine-grained control over async workflows without relying on external storage.

  • p-queue:

    Choose p-queue if you need a lightweight, promise-based queue with support for concurrency control and rate limiting. It is ideal for projects that require fine-tuned control over the number of concurrent tasks without the need for external storage.

  • queue:

    Choose queue if you need a simple, in-memory FIFO queue with support for concurrency and task prioritization. It is suitable for lightweight applications that require basic queue functionality without external dependencies.

  • bull:

    Choose bull if you need a feature-rich, Redis-based queue with support for job prioritization, retries, rate limiting, and more. It is ideal for applications that require advanced queue management features and scalability.

  • agenda:

    Choose agenda if you need a MongoDB-backed job scheduler with support for recurring tasks and a simple API. It is ideal for applications that require persistent job storage and scheduling capabilities.

  • bee-queue:

    Choose bee-queue if you need a high-performance, Redis-backed job queue optimized for fast processing and low latency. It is designed for applications that require efficient handling of large volumes of jobs with minimal overhead.

  • kue:

    Choose kue if you need a simple, Redis-backed priority job queue with a built-in UI for monitoring. It is suitable for applications that require basic queue functionality with an easy-to-use interface for tracking job status.

README for async

Async Logo

Github Actions CI status NPM version Coverage Status Join the chat at https://gitter.im/caolan/async jsDelivr Hits

Async is a utility module which provides straight-forward, powerful functions for working with asynchronous JavaScript. Although originally designed for use with Node.js and installable via npm i async, it can also be used directly in the browser. An ESM/MJS version is included in the main async package that should automatically be used with compatible bundlers such as Webpack and Rollup.

A pure ESM version of Async is available as async-es.

For Documentation, visit https://caolan.github.io/async/

For Async v1.5.x documentation, go HERE

// for use with Node-style callbacks...
var async = require("async");

var obj = {dev: "/dev.json", test: "/test.json", prod: "/prod.json"};
var configs = {};

async.forEachOf(obj, (value, key, callback) => {
    fs.readFile(__dirname + value, "utf8", (err, data) => {
        if (err) return callback(err);
        try {
            configs[key] = JSON.parse(data);
        } catch (e) {
            return callback(e);
        }
        callback();
    });
}, err => {
    if (err) console.error(err.message);
    // configs is now a map of JSON data
    doSomethingWith(configs);
});
var async = require("async");

// ...or ES2017 async functions
async.mapLimit(urls, 5, async function(url) {
    const response = await fetch(url)
    return response.body
}, (err, results) => {
    if (err) throw err
    // results is now an array of the response bodies
    console.log(results)
})