Cito – Actionable data observability for data teams
Hi HN! We’re Clemens and Felix from Cito - thrilled to show you what we’ve built to help data engineers stay on top of data quality issues. Think Datadog meets Incident.io. Tests in dbt are great when checking whether specific expectations are true, but don’t work well for use cases where data patterns may change over time. When relying on testing alone, data teams regularly face situations where business stakeholders identify data issues in dashboards first, eroding trust. In such situations, understanding the implications of an issue and debugging can be a very manual and time-consuming…
Cito – Actionable data observability for data teams launched on November 8, 2022 with 36 votes, #1,109 of 3,471 launches that month and more than 75% of that year's launches.
In plain words
Cito is a data observability platform that helps data teams detect and respond to data quality issues. It monitors data pipelines using anomaly detection and custom tests to identify problems like row count changes and schema shifts, then provides context for debugging and impact analysis. Built for data engineers who need to catch issues before business stakeholders discover them in dashboards, Cito combines monitoring capabilities with incident management features to reduce manual investigation time.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN! We’re Clemens and Felix from Cito - thrilled to show you what we’ve built to help data engineers stay on top of data quality issues. Think Datadog meets Incident.io. Tests in dbt are great when checking whether specific expectations are true, but don’t work well for use cases where data patterns may change…
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