Compares vectors based on the angle between them, which allows you to
measure similarity that isn't based on the vectors magnitude.
We recommend using DOT_PRODUCT with unit normalized vectors instead of
COSINE distance, which is mathematically equivalent with better
performance. See Cosine
Similarity to learn
more.
DotProduct
Similar to cosine but is affected by the magnitude of the vectors. See
Dot Product to learn more.
Euclidean
Measures the EUCLIDEAN distance between the vectors. See
Euclidean to learn
more
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[[["\u003cp\u003eThis document provides reference documentation for the \u003ccode\u003eDistanceMeasure\u003c/code\u003e enum within the \u003ccode\u003eStructuredQuery.Types.FindNearest.Types\u003c/code\u003e namespace of the Firestore v1 API.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eDistanceMeasure\u003c/code\u003e enum specifies how vectors are compared, offering options like \u003ccode\u003eCosine\u003c/code\u003e, \u003ccode\u003eDotProduct\u003c/code\u003e, and \u003ccode\u003eEuclidean\u003c/code\u003e, each with distinct characteristics and mathematical foundations.\u003c/p\u003e\n"],["\u003cp\u003eThe latest available version for this specific documentation is 3.10.0, though there are version history entries going back to version 2.3.0.\u003c/p\u003e\n"],["\u003cp\u003eThe enum contains a fourth option, \u003ccode\u003eUnspecified\u003c/code\u003e, which should not be set.\u003c/p\u003e\n"]]],[],null,[]]
