DatriseAI-first ETL

Yandex Metrica to PostgreSQL Integration

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

How Datrise loads Yandex Metrica into PostgreSQL

Datrise syncs Yandex Metrica's sessions, visitors, pageviews, traffic sources, goals, and user parameters into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Yandex Metrica: Website traffic analytics and session recordings.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Yandex Metrica entities map to PostgreSQL

Yandex Metrica entityPostgreSQL objectNotes
sessionsyandex_metrica_sessionsid PK · custom fields → jsonb columns
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 PostgreSQL?

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

How does the Yandex Metrica to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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