Async rate limiter


Bottleneck is a tiny and efficient Asynchronous Rate Limiter for Node.JS and the browser. When dealing with services with limited resources, it's important to ensure that they don't become overloaded.

Bottleneck is the easiest solution as it doesn't add any complexity to the code.

It's battle-hardened, reliable and production-ready. uses it to serve millions of queries per day.



npm install bottleneck


bower install bottleneck


<script type="text/javascript" src="bottleneck.min.js"></script>


Most APIs have a rate limit. For example, the API limits programs to 1 request every 2 seconds.

var Bottleneck = require("bottleneck"); //Node only 
// Never more than 1 request running at a time. 
// Wait at least 2000ms between each request. 
var limiter = new Bottleneck(1, 2000);

Instead of doing

someAsyncCall(arg1, arg2, argN, callback);

You do

limiter.submit(someAsyncCall, arg1, arg2, argN, callback);

And now you can be assured that someAsyncCall will abide by your rate guidelines!

Bottleneck builds a queue of requests and executes them as soon as possible. All the requests will be executed in order.

This is sufficient for the vast majority of applications. Read the Gotchas section and you're good to go. Or keep reading to learn about all the fine tuning available for the more complex cases.



var limiter = new Bottleneck(maxConcurrent, minTime, highWater, strategy);
  • maxConcurrent : How many requests can be running at the same time. Default: 0 (unlimited)
  • minTime : How long to wait after launching a request before launching another one. Default: 0ms
  • highWater : How long can the queue get? Default: 0 (unlimited)
  • strategy : Which strategy to use if the queue gets longer than the high water mark. Default: Bottleneck.strategy.LEAK.


Adds a request to the queue.

limiter.submit(someAsyncCall, arg1, arg2, argN, callback);

It returns true if the strategy was executed.


  • If a callback isn't necessary, you must pass null or an empty function instead.

  • Make sure that all the requests will eventually complete! This is very important if you are using a maxConcurrent value that isn't 0 (unlimited), otherwise those uncompleted requests will be clogging up the limiter and no new requests will be getting through. A way to do this is to use a timer that will always call the callback. It's safe to call the callback more than once, subsequent calls are ignored.


A strategy is a simple algorithm that is executed every time submit would cause the queue to exceed highWater.

#####Bottleneck.strategy.LEAK When submitting a new request, if the queue length reaches highWater, drop the oldest request in the queue. This is useful when requests that have been waiting for too long are not important anymore.

#####Bottleneck.strategy.OVERFLOW When submitting a new request, if the queue length reaches highWater, do not add the new request.

#####Bottleneck.strategy.BLOCK When submitting a new request, if the queue length reaches highWater, the limiter falls into "blocked mode". All queued requests are dropped and no new requests will be accepted into the queue until the limiter unblocks. It will unblock after penalty milliseconds have passed without receiving a new request. penalty is equal to 15 * minTime (or 5000 if minTime is 0) by default and can be changed by calling changePenalty(). This strategy is ideal when bruteforce attacks are to be expected.



If a request was submitted right now, would it be run immediately? Returns a boolean.



Cancels all queued up requests and prevents additonal requests from being submitted.

  • interrupt : If true, prevent the requests currently running from calling their callback when they're done. Default: false


limiter.changeSettings(maxConcurrent, minTime, highWater, strategy);

Same parameters as the constructor, pass null to skip a parameter and keep it to its current value.

Note: Changing maxConcurrent and minTime will not affect requests that have already been scheduled for execution.

For example, imagine that 3 60-second requests are submitted at time T+0 with maxConcurrent = 0 and minTime = 2000. The requests will be launched at T+0 seconds, T+2 seconds and T+4 seconds respectively. If right after adding the requests to Bottleneck, you were to call limiter.changeSettings(1);, it won't change the fact that there will be 3 requests running at the same time for roughly 60 seconds. Once again, changeSettings only affects requests that have not yet been submitted.

This is by design, as Bottleneck made a promise to execute those requests according to the settings valid at the time. Changing settings afterwards should not break previous assumptions, as that would make code very error-prone and Bottleneck a tool that cannot be relied upon.



This changes the penalty value used by the BLOCK strategy.

###changeReservoir(), incrementReservoir()

  • reservoir : How many requests can be executed before the limiter stops executing requests. Default: null (unlimited)

If reservoir reaches 0, no new requests will be executed until it is no more 0

##Execution guarantee

Bottleneck will execute every submitted request in order. They will all eventually be executed as long as:

  • highWater is set to 0 (default), which prevents the strategy from ever being run.
  • maxConcurrent is set to 0 (default) OR all requests call the callback eventually.
  • reservoir is null (default).


The main design goal for Bottleneck is to be extremely small and transparent to use. It's meant to add the least possible complexity to the code.

Let's take a DNS server as an example of how Bottleneck can be used. It's a service that sees a lot of abuse. Bottleneck is so tiny, it's not unreasonable to create one instance of it for each origin IP, even if it means creating thousands of instances. The BLOCK strategy will then easily lock out abusers and prevent the server from being used for a DNS amplification attack.

Other times, the application acts as a client and Bottleneck is used to not overload the server. In those cases, it's often better to not set any highWater mark so that no request is ever lost.

Most of the time, using Bottleneck is as simple as the first example above. However, when Bottleneck is used on a synchronous call, it (obviously) becomes asynchronous, so the returned value of that call can't be used directly. The following example should make it clear why.

This is the original code that we want to rate-limit:

var req = http.request(options, function(res){
    //do stuff with res 
req.write("some string", "utf8");

The following code snippet will NOT work, because http.request is not executed synchronously therefore req doesn't contain the expected request object.

var req = limiter.submit(http.request, options, function(res){
    //do stuff with res 
req.write("some string", "utf8");

This is the right way to do it:

    var req = http.request(options, function(res){
        //do stuff with res 
    req.write("some string", "utf8");
}, null);


This README file is always in need of better explanations and examples. If things can be clearer and simpler, please consider forking this repo and submitting a Pull Request.

Suggestions and bug reports are also welcome.