Most autocomplete implementations I've seen do full-list scanning and simple (infix) text matching.

The standard performance optimizations seem to be complex: indexing, caching, tries, etc.

This library is a simpler and much faster "back end" for autocompletes. It isn't as full-featured, which means it can make some assumptions for really big perf wins, namely:

1. It only does prefix matching.

In my experience this actually makes perfect sense in a lot of cases. For example suppose your user is searching for a company name; they aren't going to type "o" or "e" to search for Home Depot. Or say they're using a dictionary; they aren't going to type "n" to search for anagram.

See for yourself how fast this is in practice: the demo uses this library to provide autocomplete results from WordNet, with close to 150,000 words. Results are pretty much instantaneous.

// constructor

var matcher = new FastMatcher(list, options);

// getting matches

var matches = matcher.getMatches(prefix);

// full example

var list = [
  { x: 'foo' },
  { x: 'bar' },
  { x: 'baz' }
];

var matcher = new FastMatcher(list, {
  // the property, or array of properties, to base matches on
  selector: 'x',

  // duh, what do you think this does?
  caseInsensitive: true,

  // return matches in their original order
  preserveOrder: true,

  // whether to match against any word (not just first) for each string
  anyWord: false,

  // how many matches to find at a time
  limit: 25
});

matcher.getMatches('ba');
// => [{ x: 'bar' }, { x: 'baz' }]

It's really not complicated. When you construct a FastMatcher instance, it creates a copy of the source list, sorted (by the property you specified with the selector option, if provided). Then when you call getMatches it does a binary search for the given prefix in the sorted list, and just iterates from that spot until (a) reaching the limit or (b) hitting an item that doesn't match.

Binary search is really, really fast.

Maybe. Probably. I don't know.