No description, website, or topics provided.
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

Trie experiments

This is an experimental implementation of a trie, which is a key/value-mapping and a persistent data structure. It is more cache aware / sensitive for access patterns than HAMT, so it is difficult to benchmark versus other persistent data structures, but initial experiments indicates it might be twice as fast as immutable-js, which seems faster than mori.

The vision is a compact key/value-datastructure/database, that can be synchronised to disk and across network, and is also useful for functional-reactive-programming. The intention is to merge ideas from the Trie, the B-Tree and compressed/succint datastructures.

Currently this is just initial steps.

Bon - Binary Object Notation

The trie works only with binary data. To store strings and other objects, they need to be encoded into byte arrays. The following properties are desired:

  • Fast, - for every key lookup/store, the key has to be converted to a byte array, so the encoding needs to be fast, - preliminary benchmark shows that Bon is about twice as fast as JSON.stringify.
  • Prefix-free, - No encoded object should be a prefix of another, - this makes the trie-implementation simpler, as data is only stored in the leafs. Example: the string "the" is a prefix of "there", but zero-terminated strings "the\0" is not a prefix of "there\0".
  • Compact - the shorter the better, though for tradeofs it is generally a higher priority to be fast.
  • Different data types, - not only strings, but also integers, numbers, objects, arrays, ... should be encodeable
  • Order preserving. The lexicograhical sorted binary strings should preserver the order of the sorted strings, ie "hello" < "hi", and -10 < -5 < 20 < 300 < 1000. For performance reason order of floating point numbers are not preserved.



  • prefix-free strings are easily enforced, and thus data is only stored in leafs / empty nodes
  • special case for unary nodes and binary nodes for performance yields better performance
  • sorted-node ie. linear list of symbols, binary search during lookup.
  • 4+4-node, ie two levels of 16-entry tables (second level only allocated when needed).


  • performance of 4+4 and linear nodes are quite similar, though for < 50 symbols linear are typically peforms better, and vice versa.
  • large performance degradation when linear nodes crosses the 127-symbol size on spidermonkey/firefox.