DatriseAI-first ETL

Source connector

YouTube Analytics connector

YouTube Analytics integration for databases, warehouses and BI tools

Channel and video performance reporting. Datrise captures YouTube Analytics entities such as videos, channels, views, watch time, subscribers and traffic sources, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

Of the 6 objects, 6 sync as upserts keyed on the primary key and 0 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `youtube_analytics_videos`) with a schema derived from the YouTube Analytics API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the YouTube Analytics pipeline page, and join the waitlist to get the YouTube Analytics connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What YouTube Analytics data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

ObjectLanding tableSync mode
videosyoutube_analytics_videosUpsert by primary key, incremental on updated-at
channelsyoutube_analytics_channelsUpsert by primary key, incremental on updated-at
viewsyoutube_analytics_viewsUpsert by primary key, incremental on updated-at
watch timeyoutube_analytics_watch_timeUpsert by primary key, incremental on updated-at
subscribersyoutube_analytics_subscribersUpsert by primary key, incremental on updated-at
traffic sourcesyoutube_analytics_traffic_sourcesUpsert by primary key, incremental on updated-at

Popular destinations for YouTube Analytics

Choose a destination below to open the ready pipeline page.

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    Airtable

    Relational spreadsheet destination for ops and go-to-market teams.

    View pipeline
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    Amazon Athena

    Serverless SQL over S3 data lake tables.

    View pipeline
  • A
    Amazon DynamoDB

    Serverless key-value and document store on AWS.

    View pipeline
  • A
    Amazon QuickSight

    AWS serverless BI with SPICE and embedded analytics.

    View pipeline
  • A
    Amazon Redshift

    AWS petabyte-scale warehouse with Spectrum.

    View pipeline
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    Amazon S3 Data Lake

    Object storage landing zone for parquet and snapshots.

    View pipeline
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    Apache Superset

    Open-source BI for SQL exploration, charts, and dashboard publishing.

    View pipeline
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    Azure Data Lake Storage

    ADLS Gen2 object storage for analytics workloads.

    View pipeline
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    Azure Synapse

    Microsoft analytics workspace with SQL pools.

    View pipeline

YouTube Analytics connector FAQ

What YouTube Analytics data does the connector extract?
6 objects: videos, channels, views, watch time, subscribers and traffic sources. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the YouTube Analytics integration incremental?
Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load YouTube Analytics data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each YouTube Analytics → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your YouTube Analytics pipeline with guided onboarding

Join the waitlist to get priority access for YouTube Analytics integrations with guided setup, schema-aware mapping, and production-grade incremental sync.