YouTube Analytics to DuckDB Integration

How Datrise loads YouTube Analytics into DuckDB

Datrise syncs YouTube Analytics's videos, channels, views, watch time, subscribers, and traffic sources into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

YouTube Analytics: Channel and video performance reporting.

DuckDB: In-process analytics database for fast local OLAP.

How YouTube Analytics entities map to DuckDB

YouTube Analytics entity	DuckDB object	Notes
videos	`youtube_analytics_videos`	id PK · custom fields → JSON or STRUCT columns
channels	`youtube_analytics_channels`	id PK · linked to youtube_analytics_videos
views	`youtube_analytics_views`	id PK · linked to youtube_analytics_videos
watch time	`youtube_analytics_watch_time`	id PK · linked to youtube_analytics_videos

FAQ

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

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

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

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

Connect YouTube Analytics to DuckDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.