--- title: How to Optimize Vector Search When RAM Gets Too... description: A deep dive into ANN (Approximate Nearest Neighbor) algorithms for vector search, comparing in-memory approaches like HNSW with on-disk alternatives like... canonical: https://daily.dev/posts/how-to-optimize-vector-search-when-ram-gets-too-expensive-on-disk-vs-in-memory-ann-indexes-ezniusn01 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes | daily.dev og:description: A deep dive into ANN (Approximate Nearest Neighbor) algorithms for vector search, comparing in-memory approaches like HNSW with on-disk alternatives like... og:url: https://daily.dev/posts/how-to-optimize-vector-search-when-ram-gets-too-expensive-on-disk-vs-in-memory-ann-indexes-ezniusn01 og:image: https://api.daily.dev/og/posts/ezNIUSN01.png og:image:alt: How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes 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 to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes **[Towards Data Science](https://daily.dev/sources/tds)** · 10 min read · 0 upvotes · 0 comments ## Summary A deep dive into ANN (Approximate Nearest Neighbor) algorithms for vector search, comparing in-memory approaches like HNSW with on-disk alternatives like DiskANN and SPANN. Covers how each algorithm works structurally, their RAM vs. disk storage trade-offs, and concrete cost comparisons showing RAM can cost 50x more than remote disk storage. At 100M vectors (1024 dimensions, float32), in-memory storage runs ~$6,000/month vs. ~$120/month on remote disk. Includes a decision framework: HNSW for latency-critical workloads where the index fits in RAM, DiskANN for large cost-sensitive indexes up to 1B+ vectors, and SPANN for extreme scale where even quantized RAM is too expensive. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [What Is DiskANN? Billion-Scale Vector Search Explained](https://daily.dev/posts/what-is-diskann-billion-scale-vector-search-explained-6akv6dq0s) · Couchbase · 0 upvotes · 0 comments - [HNSW vs LSH: How Elasticsearch hits 0.99 recall@10 at 15,000 QPS — and what it costs](https://daily.dev/posts/hnsw-vs-lsh-how-elasticsearch-hits-0-99-recall-10-at-15-000-qps-and-what-it-costs-sbqrpbp3z) · elastic · 0 upvotes · 0 comments - [Vector Databases Explained in 3 Levels of Difficulty](https://daily.dev/posts/vector-databases-explained-in-3-levels-of-difficulty-pg3waxjnd) · Machine Learning Mastery · 4 upvotes · 0 comments --- Tags: [#vector-search](https://daily.dev/tags/vector-search) [View this post on daily.dev](https://daily.dev/posts/how-to-optimize-vector-search-when-ram-gets-too-expensive-on-disk-vs-in-memory-ann-indexes-ezniusn01) ```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 to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes","url":"https://daily.dev/posts/how-to-optimize-vector-search-when-ram-gets-too-expensive-on-disk-vs-in-memory-ann-indexes-ezniusn01","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/how-to-optimize-vector-search-when-ram-gets-too-expensive-on-disk-vs-in-memory-ann-indexes-ezniusn01"},"datePublished":"2026-07-25T15:43:37.770Z","dateModified":"2026-07-25T16:41:33.333Z","description":"A deep dive into ANN (Approximate Nearest Neighbor) algorithms for vector search, comparing in-memory approaches like HNSW with on-disk alternatives like...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/a0346b8352a737471c363ed6b21d7124?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/a0346b8352a737471c363ed6b21d7124?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Towards Data Science","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":"Towards Data Science","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/tds","url":"https://daily.dev/sources/tds"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/how-to-optimize-vector-search-when-ram-gets-too-expensive-on-disk-vs-in-memory-ann-indexes-ezniusn01","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"vector-search","timeRequired":"PT10M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Towards Data Science","item":"https://daily.dev/sources/tds"},{"@type":"ListItem","position":3,"name":"How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes"}]} ```