--- title: AWS Introduces Native Vector Search for DynamoDB | daily.dev description: Amazon DynamoDB now supports native vector search, letting developers store embeddings alongside application data and run approximate nearest-neighbor queries... canonical: https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: AWS Introduces Native Vector Search for DynamoDB | daily.dev og:description: Amazon DynamoDB now supports native vector search, letting developers store embeddings alongside application data and run approximate nearest-neighbor queries... og:url: https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z og:image: https://api.daily.dev/og/posts/nn2Cx8I4Z.png og:image:alt: AWS Introduces Native Vector Search for DynamoDB 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. # AWS Introduces Native Vector Search for DynamoDB **[InfoQ](https://daily.dev/sources/infoq)** · 4 min read · 0 upvotes · 0 comments ## Summary Amazon DynamoDB now supports native vector search, letting developers store embeddings alongside application data and run approximate nearest-neighbor queries directly via a new SearchVectors API, eliminating the need to sync data to a separate vector database. It supports up to 4096 dimensions, Euclidean, Cosine, and Dot product distance functions, inline filtering, and horizontal scaling with no storage limits. Pricing is based on data written, processed during search, and stored, each billed per GB. Community reaction is largely positive, though some note AWS is late compared to other databases that already added vector support, and others question cost versus alternatives like S3 vector buckets. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How do I do vector search in DynamoDB without a separate vector database? DynamoDB now supports native vector search through a new index type built on vector embeddings stored in table attributes. Create a vector index with the required dimensions and distance function, choose an embedding model such as Bedrock Titan, Cohere Embed, or OpenAI embeddings, and query using the new SearchVectors API, avoiding a separate synced vector database. _Track new database capabilities like this on daily.dev as AI-driven architecture choices evolve._ ### What are the dimension and distance function limits for DynamoDB vector search? DynamoDB vector indexes support up to 4096 dimensions and offer Euclidean, Cosine, and Dot product distance functions, along with inline filtering. Vector indexes have no storage limits and scale horizontally as data grows, remaining fully serverless with no infrastructure to manage. _Developers evaluating vector database options can follow capability comparisons like this on daily.dev._ ### How is Amazon DynamoDB vector search billed? A DynamoDB vector index is billed on three metered-per-byte, per-GB dimensions in addition to standard DynamoDB table charges: the data written into the index, the data processed during search, and the data stored. Costs can be reduced using lower dimensions, minimal index projections, excluding embeddings from results, and selective partitioning. _Teams weighing DynamoDB against alternatives like S3 vector buckets can track cost breakdowns on daily.dev._ ## Similar posts on daily.dev - [Amazon S3 Vectors now generally available with increased scale and performance](https://daily.dev/posts/amazon-s3-vectors-now-generally-available-with-increased-scale-and-performance-0gpqkus8w) · AWS · 0 upvotes · 0 comments - [S3 Vectors with OpenSearch: Cost-Efficient Hybrid Vector Search](https://daily.dev/posts/s3-vectors-with-opensearch-cost-efficient-hybrid-vector-search-xabkmmtbp) · BigData Boutique blog · 1 upvotes · 0 comments - [Amazon S3 Vectors Reaches GA, Introducing "Storage-First" Architecture for RAG](https://daily.dev/posts/amazon-s3-vectors-reaches-ga-introducing-storage-first-architecture-for-rag-ebcqk2lpm) · InfoQ · 0 upvotes · 0 comments - [Vector search database: news & 2026 guide](https://daily.dev/posts/vector-search-database-news-2026-guide-jn2fx26te) · Redis · 0 upvotes · 0 comments --- Tags: [#aws](https://daily.dev/tags/aws), [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search), [#nosql](https://daily.dev/tags/nosql), [#aws-dynamodb](https://daily.dev/tags/aws-dynamodb) [View this post on daily.dev](https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z) ```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":"AWS Introduces Native Vector Search for DynamoDB","url":"https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z"},"datePublished":"2026-08-16T07:28:57.639Z","dateModified":"2026-08-24T06:50:44.351Z","description":"Amazon DynamoDB now supports native vector search, letting developers store embeddings alongside application data and run approximate nearest-neighbor queries...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/51f8def3841f69c85efc86c530c27b7b?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/51f8def3841f69c85efc86c530c27b7b?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"InfoQ","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":"InfoQ","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/afc3bced3e1e4b188dd9127017a60e0c","url":"https://daily.dev/sources/infoq"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"aws,rag,vector-search,nosql,aws-dynamodb","timeRequired":"PT4M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"InfoQ","item":"https://daily.dev/sources/infoq"},{"@type":"ListItem","position":3,"name":"AWS Introduces Native Vector Search for DynamoDB"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/aws-introduces-native-vector-search-for-dynamodb-nn2cx8i4z#faq","mainEntity":[{"@type":"Question","name":"How do I do vector search in DynamoDB without a separate vector database?","acceptedAnswer":{"@type":"Answer","text":"DynamoDB now supports native vector search through a new index type built on vector embeddings stored in table attributes. 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