--- title: How Musinsa scaled its audience engine with ClickHouse... description: Musinsa, Korea's largest fashion platform with 16.4 million members, migrated its customer data platform's Audience Engine from self-hosted ClickHouse to... canonical: https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How Musinsa scaled its audience engine with ClickHouse Cloud and reduced TCO by 71.4% | daily.dev og:description: Musinsa, Korea's largest fashion platform with 16.4 million members, migrated its customer data platform's Audience Engine from self-hosted ClickHouse to... og:url: https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp og:image: https://api.daily.dev/og/posts/aj672xoCp.png og:image:alt: How Musinsa scaled its audience engine with ClickHouse Cloud and reduced TCO by 71.4% 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 Musinsa scaled its audience engine with ClickHouse Cloud and reduced TCO by 71.4% **[ClickHouse](https://daily.dev/sources/clickhouse)** · 8 min read · 0 upvotes · 0 comments ## Summary Musinsa, Korea's largest fashion platform with 16.4 million members, migrated its customer data platform's Audience Engine from self-hosted ClickHouse to ClickHouse Cloud on AWS. The move addressed scaling pain points caused by coupled compute and storage on EBS volumes, resource contention across workloads, and heavy operational overhead. After migrating, Musinsa cut storage costs by 86.5% and total cost of ownership by up to 71.4%. Compute workloads now run independently with automatic idling and vertical autoscaling. Real-time ingestion was simplified by replacing Databricks Auto Loader on a separate Spark cluster with ClickPipes, reducing both operational complexity and Databricks costs. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What cost savings did Musinsa achieve by migrating from self-hosted ClickHouse to ClickHouse Cloud? Musinsa reduced storage costs by 86.5% and total cost of ownership by up to 71.4% after migrating to ClickHouse Cloud. The gains came from separating compute and storage layers (compute nodes draw on shared S3 instead of attached EBS), running each workload on independently sized clusters, and using automatic idling so resources are only consumed when active. _Teams weighing self-hosted vs. managed ClickHouse for analytics workloads track real migration outcomes like this on daily.dev._ ### How did Musinsa replace Databricks Auto Loader in their ClickHouse ingestion pipeline? Musinsa replaced Databricks Auto Loader, which ran on a separate external Spark cluster, with ClickPipes — ClickHouse Cloud's native ingestion layer. ClickPipes ingests data directly into ClickHouse Cloud and hands off to materialized views and storage, eliminating the external Spark cluster and reducing both operational overhead and Databricks costs. _Engineers simplifying real-time ingestion pipelines away from Spark find relevant migration patterns on daily.dev._ ## Similar posts on daily.dev - [How Insider One uses ClickHouse Cloud to power real-time customer engagement at scale](https://daily.dev/posts/how-insider-one-uses-clickhouse-cloud-to-power-real-time-customer-engagement-at-scale-mzbb4iift) · ClickHouse · 0 upvotes · 0 comments - [How Suprema Gaming made its data platform agent-ready with ClickHouse Cloud](https://daily.dev/posts/how-suprema-gaming-made-its-data-platform-agent-ready-with-clickhouse-cloud-2xbhyibyo) · ClickHouse · 2 upvotes · 0 comments - [How Superwall Scales with WarpStream and ClickHouse Cloud](https://daily.dev/posts/how-superwall-scales-with-warpstream-and-clickhouse-cloud-lbdjyrqtc) · Confluent Blog · 2 upvotes · 0 comments - [Mintlify boosts NPS 30% and saves 60% with real-time analytics on ClickHouse Cloud](https://daily.dev/posts/mintlify-boosts-nps-30-and-saves-60-with-real-time-analytics-on-clickhouse-cloud-jyy9uugeq) · ClickHouse · 0 upvotes · 0 comments - [How Eisan made POS analytics faster, cheaper, and more reliable with ClickHouse Cloud](https://daily.dev/posts/how-eisan-made-pos-analytics-faster-cheaper-and-more-reliable-with-clickhouse-cloud-qxlq1g0hd) · ClickHouse · 2 upvotes · 0 comments --- Tags: [#business](https://daily.dev/tags/business), [#data-engineering](https://daily.dev/tags/data-engineering), [#clickhouse](https://daily.dev/tags/clickhouse) [View this post on daily.dev](https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp) ```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 Musinsa scaled its audience engine with ClickHouse Cloud and reduced TCO by 71.4%","url":"https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp"},"datePublished":"2026-08-10T14:59:22.252Z","dateModified":"2026-08-10T14:59:55.853Z","description":"Musinsa, Korea's largest fashion platform with 16.4 million members, migrated its customer data platform's Audience Engine from self-hosted ClickHouse to...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/d6f75ccefa60ff99685808b74b1b7244?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/d6f75ccefa60ff99685808b74b1b7244?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"ClickHouse","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":"ClickHouse","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/clickhouse","url":"https://daily.dev/sources/clickhouse"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"business,data-engineering,clickhouse","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"ClickHouse","item":"https://daily.dev/sources/clickhouse"},{"@type":"ListItem","position":3,"name":"How Musinsa scaled its audience engine with ClickHouse Cloud and reduced TCO by 71.4%"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/how-musinsa-scaled-its-audience-engine-with-clickhouse-cloud-and-reduced-tco-by-71-4--aj672xocp#faq","mainEntity":[{"@type":"Question","name":"What cost savings did Musinsa achieve by migrating from self-hosted ClickHouse to ClickHouse Cloud?","acceptedAnswer":{"@type":"Answer","text":"Musinsa reduced storage costs by 86.5% and total cost of ownership by up to 71.4% after migrating to ClickHouse Cloud. The gains came from separating compute and storage layers (compute nodes draw on shared S3 instead of attached EBS), running each workload on independently sized clusters, and using automatic idling so resources are only consumed when active. Teams weighing self-hosted vs. managed ClickHouse for analytics workloads track real migration outcomes like this on daily.dev."}},{"@type":"Question","name":"How did Musinsa replace Databricks Auto Loader in their ClickHouse ingestion pipeline?","acceptedAnswer":{"@type":"Answer","text":"Musinsa replaced Databricks Auto Loader, which ran on a separate external Spark cluster, with ClickPipes — ClickHouse Cloud's native ingestion layer. ClickPipes ingests data directly into ClickHouse Cloud and hands off to materialized views and storage, eliminating the external Spark cluster and reducing both operational overhead and Databricks costs. Engineers simplifying real-time ingestion pipelines away from Spark find relevant migration patterns on daily.dev."}}]} ```