TL;DR Sets are 2x faster in this benchmark. Please be cautious and don't generalize this statement to all Set operations.

Counting unique elements is a common task in many programs. Until recently the most straightforward way to do so was something along these lines:

function getUniqueElements(array) {
  var counter = {};
  for (var i = 0; i < array.length; ++i) {
    var key = array[i];
    counter[key] = 1;
  }
  return Object.keys(counter);
}

var unique = getUniqueElements(["cat", "dog", "cat"]);
// unique is: ['cat', 'dog']

SIDE NOTE: This program has a subtle bug. Open issue if you found it and I'll give you credit. Kudos to @lukaszsamson, @erykpiast, @elclanrs, @Slayer95 and @bchelli for bringing answers!

With introduction of Set object things have changed. The program can be rewritten as:

function getUniqueSet(array) {
  return new Set(array);
}

var uniqueSet = getUniqueSet(["cat", "dog", "cat"]);
// uniqueSet now has only two elements 'cat' and 'dog'.

Set is supported by all major browsers but is it really faster than plain old Object?

Jaccard similarity is a simple function which takes two sets and returns their "similarity" index:

function similarity(A, B) {
  intersection = (number of shared elements between A and B)
  union = (number of unique elements in A and B)

  return intersection/union
}

For example, similarity between set cat, dog, bird and set cat is 1/3. There is one shared element (cat), and there are three unique elements.

Now we have to implement this function two times: using Set and using Object:

function similarityObject(objA, objB) {
  var aKeys = Object.keys(objA);
  var intersect = 0;
  aKeys.forEach(function(key) {
    if (objB[key]) intersect += 1;
  });
  var objBSize = Object.keys(setB).length;
  var objASize = aKeys.length;
  var similarity = intersect / (objASize + objBSize - intersect);

  return similarity;
}

function similaritySet(setA, setB) {
  var intersect = 0;
  setA.forEach(function(key) {
    if (setB.has(key)) intersect += 1;
  });
  var similarity = intersect / (setA.size + setB.size - intersect);

  return similarity;
}

To have statistically reliable answers we run these functions over and over again on the same data set and count how many times we were able to compute similarity index. Benchmark module is extremely good for this. Here are the results:

> node index.js
Compute jaccard similarity with Set x 3,445 ops/sec ±2.39% (84 runs sampled)
Compute jaccard similarity with Map x 3,479 ops/sec ±0.40% (91 runs sampled)
Compute jaccard similarity with objects (Object.keys()) x 1,787 ops/sec ±0.97% (86 runs sampled)
Compute jaccard similarity with objects (for in) x 1,698 ops/sec ±0.75% (91 runs sampled)
Fastest is Compute jaccard similarity with Map
(Set) Jaccard top pair at: 2 (0.010101010101010102)
(Map) Jaccard top pair at: 2 (0.010101010101010102)
(Obj.keys) Jaccard top pair at: 2 (0.010101010101010102)

Set objects are two times faster than our old plain Object. The tests were executed using node version 14.4.0

I compared RAM consumption by building 1,000,000 string keys and stored them both as object keys and as set elements. There was huge overhead of memory usage with objects.

Set used ~67MB, while Object used ~126MB:

Testing with Set
Memory usage (bytes): {
   "rss": 113,303,552,
   "heapTotal": 89,473,024,
   "heapUsed":67,126,776,
   "external":775,983
}

Testing with Object
Memory usage (bytes): {
  "rss": 155,701,248,
  "heapTotal": 131,948,544,
  "heapUsed": 126,989,976,
  "external": 775,983
}

You can read description of each field here: process.memoryUsage().

Tes code is in testMemory.sh

Sets are awesome and we should use them more often. They are fast, and supported by Chrome, Firefox, Microsoft Edge, and Node.js.

You can explore index.js file to see the actual benchmark code.

• Array vs Object - what is faster: store array of vectors, or encode vectors into array?
• Iterator vs foreach - what is faster: use forEach, for, for .. of, [Symbol.Iterator](), or yield *?

If you haven't seen it yet, watch this video about performance and benchmarking from Vyacheslav Egorov: https://www.youtube.com/watch?v=65-RbBwZQdU .

He doesn't talk about Sets or Jaccard similarity. His view on benchmarking changed how I perceive them now, and I hope you will love it too!