---
title: "How Meilisearch Updates a Millions Vector Embeddings Database in Under a Minute"
url: https://daily.dev/posts/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute-0rlxfc3wb
source_url: https://blog.kerollmops.com/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute
type: article
source: "Lobsters"
published: 2024-03-26T16:27:48.206Z
updated: 2025-09-06T02:22:10.261Z
tags: ["meilisearch"]
reading_time: 8
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# How Meilisearch Updates a Millions Vector Embeddings Database in Under a Minute

**[Lobsters](https://daily.dev/sources/lobsters)** · 8 min read · 0 upvotes · 0 comments

## Summary

This post explains how Meilisearch implemented incremental indexing in Arroy, the three kinds of nodes in the vector store based on LMDB, and the ID generation strategy used in the process.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.kerollmops.com/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute>

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---

Tags: [#meilisearch](https://daily.dev/tags/meilisearch)

[View this post on daily.dev](https://daily.dev/posts/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute-0rlxfc3wb)