DatriseAI-first ETL

Yandex Metrica to Apache Superset Integration

AI-first ETL from Yandex Metrica into Apache Superset. Governed entities, incremental sync, typed landing tables.

How Datrise loads Yandex Metrica into Apache Superset

Datrise syncs Yandex Metrica's sessions, visitors, pageviews, traffic sources, goals, and user parameters into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

Yandex Metrica: Website traffic analytics and session recordings.

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

How Yandex Metrica entities map to Apache Superset

Yandex Metrica entityApache Superset objectNotes
sessionsyandex_metrica_sessionsid PK · custom fields → flattened columns for the explore UI
visitorsyandex_metrica_visitorsid PK · linked to yandex_metrica_sessions
pageviewsyandex_metrica_pageviewsid PK · linked to yandex_metrica_sessions
traffic sourcesyandex_metrica_traffic_sourcesid PK · linked to yandex_metrica_sessions

FAQ

How does Datrise handle Yandex Metrica's custom fields in Apache Superset?

Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.

How does the Yandex Metrica to Apache Superset sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

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