ArraysAja

Provides an Arrays implementation for Aja's Vector datatype, which is an implementation of a 'Hickey Trie' Vector written in Elixir.

Performance

Aja's implementation is fast. As can be seen from below benchmarking graphs, A.Vector beats the other alternative datatypes outright in most common tasks:

Random reads are much faster regardless of array size. (and remain super fast even for very large arrays!)
Random updates are slightly (~20%) slower than using an MapArray or ErlangArray for arrays with less than ~2^1 elements. After this, A.Vector is often much faster. (I do not yet know what causes the odd spike at 2^17 where A.Vector is super fast.)
Appending a single element is similarly performant to the other implementations. At higher sizes, it keeps up with ErlangArray (where MapArray becomes much slower.)
Concatenating is where A.Vector also really shines: It is roughly 5x(!) faster than ErlangArray and MapArray, regardless of collection size. It is only outclassed by plain lists (which are again ~5x faster for concatenation, but much (i.e. asymptotically) slower for all of the other three operations).

random_read random_update append append append concat concat concat concat

Installation

ArraysAja is available in Hex, and can be installed by adding arrays_aja to your list of dependencies in mix.exs:

def deps do
  [
    {:arrays_aja, "~> 0.2.0"}
  ]
end

Documentation can be found at https://hexdocs.pm/arrays_aja.