--- title: Behind the hype: managing billion-scale embeddings in... description: A conference talk covering practical strategies for managing billion-scale vector embeddings in Elasticsearch and OpenSearch. Topics include chunking... canonical: https://daily.dev/posts/behind-the-hype-managing-billion-scale-embeddings-in-elasticsearch-and-opensearch-by-pietro-mele-cl2xbbnxk twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Behind the hype: managing billion-scale embeddings in Elasticsearch and OpenSearch by Pietro Mele | daily.dev og:description: A conference talk covering practical strategies for managing billion-scale vector embeddings in Elasticsearch and OpenSearch. Topics include chunking... og:url: https://daily.dev/posts/behind-the-hype-managing-billion-scale-embeddings-in-elasticsearch-and-opensearch-by-pietro-mele-cl2xbbnxk og:image: https://api.daily.dev/og/posts/Cl2xbbNxK.png og:image:alt: Behind the hype: managing billion-scale embeddings in Elasticsearch and OpenSearch by Pietro Mele 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. # Behind the hype: managing billion-scale embeddings in Elasticsearch and OpenSearch by Pietro Mele **[Devoxx](https://daily.dev/sources/devoxx)** · 44 min read · 0 upvotes · 0 comments ## Summary A conference talk covering practical strategies for managing billion-scale vector embeddings in Elasticsearch and OpenSearch. Topics include chunking strategies, model selection for vectorization, GPU-accelerated indexing with CAGRA, disk and RAM requirements at scale, approximate nearest neighbor algorithms (HNSW and IVF), scalar/product/binary quantization techniques to reduce memory from ~4TB to hundreds of GB, and disk-based vector search options. Key takeaways: quantization with reranking is essential at billion-vector scale, disabling source storage for vector fields saves significant space, and both platforms are rapidly improving their vector search capabilities. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Scaling Vector Search Performance: From Millions to Billions](https://daily.dev/posts/scaling-vector-search-performance-from-millions-to-billions-c5dvchkfu) · BigData Boutique blog · 3 upvotes · 0 comments - [Scaling Vector Search with OpenSearch](https://daily.dev/posts/scaling-vector-search-with-opensearch-cu8mrge1x) · BigData Boutique blog · 5 upvotes · 1 comments - [Decoupled by Design: Billion-Scale Vector Search](https://daily.dev/posts/decoupled-by-design-billion-scale-vector-search-puyxn3eah) · databricks · 26 upvotes · 0 comments --- Tags: [#elk](https://daily.dev/tags/elk), [#vector-search](https://daily.dev/tags/vector-search), [#opensearch](https://daily.dev/tags/opensearch) [View this post on daily.dev](https://daily.dev/posts/behind-the-hype-managing-billion-scale-embeddings-in-elasticsearch-and-opensearch-by-pietro-mele-cl2xbbnxk) ```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":"Behind the hype: managing billion-scale embeddings in Elasticsearch and OpenSearch by Pietro Mele","url":"https://daily.dev/posts/behind-the-hype-managing-billion-scale-embeddings-in-elasticsearch-and-opensearch-by-pietro-mele-cl2xbbnxk","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/behind-the-hype-managing-billion-scale-embeddings-in-elasticsearch-and-opensearch-by-pietro-mele-cl2xbbnxk"},"datePublished":"2026-03-30T19:18:46.433Z","dateModified":"2026-03-30T19:19:09.289Z","description":"A conference talk covering practical strategies for managing billion-scale vector embeddings in Elasticsearch and OpenSearch. 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