DatriseAI-first ETL

Yandex Metrica ClickHouse

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

How Datrise loads Yandex Metrica into ClickHouse

Datrise syncs Yandex Metrica's records, events, and configuration objects 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

Yandex Metrica: SaaS or API data source for analytics and warehouse sync.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Yandex Metrica entities map to ClickHouse

Yandex Metrica entityClickHouse objectNotes
recordsyandex_metrica_recordsid PK · custom fields → JSON or Map columns
eventsyandex_metrica_eventsDateTime64 events
configuration objectsyandex_metrica_configuration_objectsid PK · linked to yandex_metrica_records

FAQ

How does Datrise handle Yandex Metrica'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 Yandex Metrica 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

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