p-limit vs p-queue

utility

p-limit

p-queue

Both p-limit and p-queue are JavaScript utility libraries designed to control concurrency when executing multiple asynchronous operations. p-limit provides a minimalist approach focused solely on limiting the number of promises running simultaneously, while p-queue offers a full-featured task queue with ordering, prioritization, and advanced management capabilities. Despite serving the same general purpose—preventing resource exhaustion from too many concurrent operations—they represent fundamentally different architectural approaches.

This comparison matters because choosing the wrong tool can lead to either over-engineering (using p-queue when you only need simple throttling) or under-engineering (using p-limit when you actually need task ordering and retries). Developers building simple parallel fetch operations or file processors will find p-limit's straightforward API sufficient, while those implementing job processing systems, webhook handlers, or complex API orchestration will benefit from p-queue's sophisticated features.

Head-to-Head

Bundle Size & Overhead→ p-limit wins

p-limit

Extremely lightweight with minimal overhead. The library is essentially a thin wrapper around promise execution with a counter, making it ideal for performance-critical applications where every kilobyte matters.

p-queue

Larger bundle size due to comprehensive queue infrastructure including priority handling, interval management, and event emission. The additional overhead is justified only when you need the features it provides.

API Complexity→ p-limit wins

p-limit

Dead simple API: create a limiter with a concurrency number, then wrap your promise-returning functions. No configuration objects, no event handlers, no learning curve. You can be productive in under 5 minutes.

p-queue

Rich but more complex API with multiple methods (.add, .addAll, .clear, .pause), event listeners (onSizeLessThan, onEmpty, onIdle), and configuration options (timeout, throwOnTimeout, intervalCap). Requires reading documentation.

Task Ordering & Prioritization→ p-queue wins

p-limit

No support for task ordering or prioritization. Tasks execute in the order they're added with no way to promote urgent tasks or enforce sequential processing within concurrent batches.

p-queue

First-class support for priority queues, allowing high-priority tasks to jump ahead. Guarantees FIFO order within priority levels, making it suitable for job processing where some tasks are more critical than others.

Rate Limiting Capabilities→ p-queue wins

p-limit

Only supports concurrency limiting (max N tasks at once). Cannot enforce time-based rate limits like 'max 10 requests per second' or 'max 100 requests per minute', which are common API requirements.

p-queue

Supports both concurrency limits and interval-based rate limiting via intervalCap and interval options. Can enforce '5 tasks per second' while also maintaining max concurrency, perfect for API clients with rate limits.

Error Handling & Retriestie

p-limit

No built-in error handling or retry mechanisms. Failed promises simply reject, and you must implement retry logic manually or use additional libraries. Keeps the library focused but requires more boilerplate.

p-queue

Supports timeout configuration per task and provides hooks for monitoring queue state, but doesn't include built-in retry logic either. However, the queue structure makes implementing retry patterns easier than with p-limit.

Queue Management & Observability→ p-queue wins

p-limit

No queue introspection. You cannot check how many tasks are pending, pause execution, or clear waiting tasks. It's a fire-and-forget mechanism with no visibility into internal state.

p-queue

Comprehensive queue management with .size, .pending, .pause(), .start(), .clear() methods. You can monitor queue depth, pause processing during maintenance windows, and cancel pending tasks, essential for production systems.

Verdict

Choose p-limit when you have independent, unordered asynchronous operations that simply need concurrency throttling. If you're fetching hundreds of URLs, processing files in parallel, or making database queries where order doesn't matter and failures are handled at the call site, p-limit's simplicity and minimal overhead make it the obvious choice. It's also the right pick when you're adding concurrency control to an existing codebase and want to minimize changes—just wrap your promise-returning functions and you're done.

Choose p-queue when your application requires task ordering, prioritization, or sophisticated queue management. If you're building webhook processors where some webhooks are more urgent, API clients that must respect both concurrency and rate limits, or job processing systems where you need to pause/resume processing, p-queue's additional complexity pays for itself. The overhead is negligible compared to the value of not having to implement priority queues, rate limiting, and queue management yourself. Don't use it for simple parallel fetching—that's using a backhoe when you need a shovel.

When to Use Each

If you are building a web scraper that fetches 1000 pages in parallel → use p-limit because you only need to prevent overwhelming the network with concurrent requests, and task order is irrelevant.

If you are building a webhook delivery system where premium customers' webhooks should process first → use p-queue because you need priority-based task execution and the ability to monitor queue depth for capacity planning.

If you are implementing an API client for a service with '100 requests per minute' rate limits → use p-queue because you need both interval-based rate limiting (intervalCap/interval) and concurrency control, which p-limit cannot provide.

If you are processing uploaded images in batches where each image transformation is independent → use p-limit because the simpler API and lower overhead is sufficient for parallel, unordered processing without special requirements.

Learn More

p-limit →p-queue →

Head-to-Head

Bundle Size & Overhead→ p-limit wins

p-limit

p-queue

API Complexity→ p-limit wins

p-limit

p-queue

Task Ordering & Prioritization→ p-queue wins

p-limit

No support for task ordering or prioritization. Tasks execute in the order they're added with no way to promote urgent tasks or enforce sequential processing within concurrent batches.

p-queue

Rate Limiting Capabilities→ p-queue wins

p-limit

Only supports concurrency limiting (max N tasks at once). Cannot enforce time-based rate limits like 'max 10 requests per second' or 'max 100 requests per minute', which are common API requirements.

p-queue

Error Handling & Retriestie

p-limit

p-queue

Queue Management & Observability→ p-queue wins

p-limit

No queue introspection. You cannot check how many tasks are pending, pause execution, or clear waiting tasks. It's a fire-and-forget mechanism with no visibility into internal state.

p-queue

Verdict

When to Use Each

If you are building a web scraper that fetches 1000 pages in parallel → use p-limit because you only need to prevent overwhelming the network with concurrent requests, and task order is irrelevant.