---
title: "What’s The Story With HNSW?"
url: https://daily.dev/posts/what-s-the-story-with-hnsw--lfwflv48i
source_url: https://towardsdatascience.com/whats-the-story-with-hnsw-d1402c37a44e
type: article
source: "Towards Data Science"
published: 2024-02-25T20:29:55.114Z
updated: 2025-09-06T02:49:06.703Z
tags: ["algorithms", "data-structures", "graph-theory", "machine-learning"]
reading_time: 8
upvotes: 1
comments: 0
language: en
---

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# What’s The Story With HNSW?

**[Towards Data Science](https://daily.dev/sources/tds)** · 8 min read · 1 upvotes · 0 comments

## Summary

HNSW is an effective approach for approximate nearest neighbor search. It uses small world graphs that connect local points and have short paths between distant points. HNSW improves upon NSW by using long-range hubs as entry points, limiting the number of connections checked at each hub, and introducing a hierarchy of layers with different connection lengths.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/whats-the-story-with-hnsw-d1402c37a44e>

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---

Tags: [#algorithms](https://daily.dev/tags/algorithms), [#data-structures](https://daily.dev/tags/data-structures), [#graph-theory](https://daily.dev/tags/graph-theory), [#machine-learning](https://daily.dev/tags/machine-learning)

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