DatriseAI-first ETL

Google Cloud SQL ClickHouse

AI-first ETL from Google Cloud SQL into ClickHouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Cloud SQL into ClickHouse

Datrise syncs Google Cloud SQL'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

Google Cloud SQL: SaaS or API data source for analytics and warehouse sync.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Google Cloud SQL entities map to ClickHouse

Google Cloud SQL entityClickHouse objectNotes
recordsgoogle_cloud_sql_recordsid PK · custom fields → JSON or Map columns
eventsgoogle_cloud_sql_eventsDateTime64 events
configuration objectsgoogle_cloud_sql_configuration_objectsid PK · linked to google_cloud_sql_records

FAQ

How does Datrise handle Google Cloud SQL'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 Google Cloud SQL 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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