How to find "k" nearest embeddings in a space with a very large number of N embeddings (efficiently)?

This page summarizes the projects mentioned and recommended in the original post on /r/MLQuestions
nearest-neighbor-search approximate-nearest-neighbor-search Recommender Systems C++ knn-graphs

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  • annoy

    Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

    • If you just want quick in memory search then pynndescent is a decent option: it's easy to install, and easy to get running. Another good option is Annoy; it's just as easy to install and get running with python, but it is a little less performant if you want to do a lot of queries, or get a knn-graph quickly.

  • pynndescent

    A Python nearest neighbor descent for approximate nearest neighbors

    • If you just want quick in memory search then pynndescent is a decent option: it's easy to install, and easy to get running. Another good option is Annoy; it's just as easy to install and get running with python, but it is a little less performant if you want to do a lot of queries, or get a knn-graph quickly.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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