DatriseAI-first ETL

YouTube Analytics to ClickHouse Integration

AI-first ETL from YouTube Analytics into ClickHouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads YouTube Analytics into ClickHouse

Datrise syncs YouTube Analytics's videos, channels, views, watch time, subscribers, and traffic sources into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

YouTube Analytics: Channel and video performance reporting.

ClickHouse: Columnar OLAP engine for fast aggregations.

How YouTube Analytics entities map to ClickHouse

YouTube Analytics entityClickHouse objectNotes
videosyoutube_analytics_videosid PK · custom fields → JSON or Map columns
channelsyoutube_analytics_channelsid PK · linked to youtube_analytics_videos
viewsyoutube_analytics_viewsid PK · linked to youtube_analytics_videos
watch timeyoutube_analytics_watch_timeid PK · linked to youtube_analytics_videos

FAQ

How does Datrise handle YouTube Analytics's custom fields in ClickHouse?

Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.

How does the YouTube Analytics to ClickHouse sync stay up to date?

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

Early access

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