--- title: How Meilisearch Updates a Millions Vector Embeddings... description: 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... canonical: https://daily.dev/posts/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute-0rlxfc3wb twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How Meilisearch Updates a Millions Vector Embeddings Database in Under a Minute | daily.dev og:description: 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... og:url: https://daily.dev/posts/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute-0rlxfc3wb og:image: https://api.daily.dev/og/posts/0rlxFC3wb.png og:image:alt: How Meilisearch Updates a Millions Vector Embeddings Database in Under a Minute og:image:width: 1200 og:image:height: 630 og:locale: 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: --- 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) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"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","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute-0rlxfc3wb"},"datePublished":"2024-03-26T16:27:48.206Z","dateModified":"2025-09-06T02:22:10.261Z","description":"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...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/b916d6bb4eeb705344c9b6ae06449330?_a=AQAEufR","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/b916d6bb4eeb705344c9b6ae06449330?_a=AQAEufR","isAccessibleForFree":true,"articleSection":"Lobsters","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Lobsters","logo":"https://media.daily.dev/image/upload/s--tl8v_Fku--/f_auto,t_logo/v1698841318/logos/lobste.jpg","url":"https://daily.dev/sources/lobsters"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/how-meilisearch-updates-a-millions-vector-embeddings-database-in-under-a-minute-0rlxfc3wb","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"meilisearch","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Lobsters","item":"https://daily.dev/sources/lobsters"},{"@type":"ListItem","position":3,"name":"How Meilisearch Updates a Millions Vector Embeddings Database in Under a Minute"}]} ```