I wrote a Julia package ( Shrike.jl ) for approximate nearest neighbor search. My algorithm draws heavily on the mrpt algorithm and uses the same principles behind annoy (a popular approximate nearest neighbor package by Spotify). My Julia implementation beat both of them! See the Shrike.jl/README.md …

This looks great! Have you considered porting it to MLJ .jl? They currently have 150+ supported models (including NearestNeighborModels.jl).

Great! Is this package comparable to the widely used and extremely efficient NearestNeighbors.jl? If yes, can you benchmark against as well? That would be a good reference to have.

[image] juliohm: NearestNeighbors.jl He does this exact benchmark in the readme IIUC

I see the plots now. I wish they were numbers though with comparable scenarios in the sense that each parameter combination is “equivalent”. I cannot fully support the statement in the README that says: It is important to note that NearestNeighbors.jl was designed to return the exact k-nearest-nei…

[image] djpasseyjr: I was shocked and thrilled! I am no Julia expert, but the fact that I was able to outperform about 2000 lines of C++ in 500 lines of Julia is a real testament to the power of the language. Glancing at your code, it should be possible to make it faster still — it seems like…

Just as a note regarding NearestNeighbors.jl, due to curse of dimensionality, the kd-tree becomes very bad for high dimensional data ( k-d tree - Wikipedia ) You want something like N >> 2^k to use it where N is the number of points and k is the dimension. The original motivation of NearestNeighbors.…

Super interested in this! Can you point me to some resources for learning how to do this? What parts of the code are you referring to?

Very nice work. I too have implemented ANN algorithms in Julia (unreleased so far) which perform comparable to C++ implementations in vastly fewer lines of code. Have you seen http://ann-benchmarks.com/ ? It would be good to get this in there for a more comprehensive comparison.

For example, on the function traverse_tree you could probably preallocate the mask array and the _get_split array. Which would increase performance a little bit.

The way I see it, it depends on what you need. If you need the exact k nearest neighbors, then stick with NearestNeighbors.jl. If 80% of the exact nearest neighbors (with the remaining being 20% points that are close) is good enough, then you can get a speed boost by using an approximate nearest nei…

[ANN] Shrike.jl: Julia beats optimized C++ (Fast accurate approximate nearest neighbor search)

Package Announcements

Topic		Replies	Views
Alternative packages for nearest neighbor search General Usage package , alternatives	2	166	July 9, 2025
Neighborhood.jl: Unified API for finding nearest neighbors in Julia Package Announcements package	15	2562	February 13, 2021
NearestNeighbors.jl: 10 year anniversary, "recent" updates and developments Community	6	914	December 16, 2025
K nearest neighbor utility in Julia Community	13	4034	February 3, 2021
[ANN] Faiss.jl, similarity search General Usage package , announcement	18	1912	March 27, 2022

[ANN] Shrike.jl: Julia beats optimized C++ (Fast accurate approximate nearest neighbor search)

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