--- title: How Trigger.dev is using ClickHouse to scale... description: Trigger.dev, a serverless async workflow platform for AI agents, migrated its observability stack from Postgres to ClickHouse to handle growing telemetry... canonical: https://daily.dev/posts/how-trigger-dev-is-using-clickhouse-to-scale-observability-for-long-running-ai-workflows-1urnkfdl2 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How Trigger.dev is using ClickHouse to scale observability for long-running AI workflows | daily.dev og:description: Trigger.dev, a serverless async workflow platform for AI agents, migrated its observability stack from Postgres to ClickHouse to handle growing telemetry... og:url: https://daily.dev/posts/how-trigger-dev-is-using-clickhouse-to-scale-observability-for-long-running-ai-workflows-1urnkfdl2 og:image: https://api.daily.dev/og/posts/1URnKfdL2.png og:image:alt: How Trigger.dev is using ClickHouse to scale observability for long-running AI workflows 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 Trigger.dev is using ClickHouse to scale observability for long-running AI workflows **[ClickHouse](https://daily.dev/sources/clickhouse)** · 8 min read · 0 upvotes · 0 comments ## Summary Trigger.dev, a serverless async workflow platform for AI agents, migrated its observability stack from Postgres to ClickHouse to handle growing telemetry volumes across thousands of tenants. Postgres struggled with large analytical workloads on a single growing table, creating reliability risks and query performance issues. After evaluating alternatives including DuckDB and ParadeDB, the team chose ClickHouse for its proven OLAP performance, open-source model, and growing ecosystem among observability-focused developer tools. The migration was gradual and zero-downtime, routing new runs to ClickHouse while legacy data remained in Postgres. Results include P95 query latency of ~200ms on tens of thousands of rows, dramatically reduced storage footprint, and new product capabilities like aggregated usage metrics via materialized views that would have been impractical in Postgres. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Shopify powers observability for global-scale commerce with ClickHouse](https://daily.dev/posts/shopify-powers-observability-for-global-scale-commerce-with-clickhouse-r45dmqcus) · ClickHouse · 3 upvotes · 0 comments - [Switching from PostgreSQL to ClickHouse for Improved Performance and Scalability](https://daily.dev/posts/switching-from-postgresql-to-clickhouse-for-improved-performance-and-scalability-kjtwee69g) · InfoQ · 5 upvotes · 0 comments - [Postgres \+ ClickHouse: The OSS Stack To Handle Agentic AI Scale](https://daily.dev/posts/postgres-clickhouse-the-oss-stack-to-handle-agentic-ai-scale-porzekft6) · The New Stack · 1 upvotes · 0 comments - [Have you heard? Clickhouse is winning the observability wars\!](https://daily.dev/posts/have-you-heard-clickhouse-is-winning-the-observability-wars--5bpefin3l) · Charity · 18 upvotes · 0 comments --- Tags: [#database](https://daily.dev/tags/database), [#postgresql](https://daily.dev/tags/postgresql), [#observability](https://daily.dev/tags/observability), [#clickhouse](https://daily.dev/tags/clickhouse) [View this post on daily.dev](https://daily.dev/posts/how-trigger-dev-is-using-clickhouse-to-scale-observability-for-long-running-ai-workflows-1urnkfdl2) ```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 Trigger.dev is using ClickHouse to scale observability for long-running AI workflows","url":"https://daily.dev/posts/how-trigger-dev-is-using-clickhouse-to-scale-observability-for-long-running-ai-workflows-1urnkfdl2","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/how-trigger-dev-is-using-clickhouse-to-scale-observability-for-long-running-ai-workflows-1urnkfdl2"},"datePublished":"2026-07-09T13:09:48.650Z","dateModified":"2026-07-09T13:10:10.665Z","description":"Trigger.dev, a serverless async workflow platform for AI agents, migrated its observability stack from Postgres to ClickHouse to handle growing telemetry...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/25cde167c6ed8c40974560a57cd203e6?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/25cde167c6ed8c40974560a57cd203e6?_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-trigger-dev-is-using-clickhouse-to-scale-observability-for-long-running-ai-workflows-1urnkfdl2","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"database,postgresql,observability,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 Trigger.dev is using ClickHouse to scale observability for long-running AI workflows"}]} ```