DatriseAI-first ETL

LinkedIn Ads ClickHouse

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

How Datrise loads LinkedIn Ads into ClickHouse

Datrise syncs LinkedIn Ads's B2B campaign metrics, spend, clicks, leads, and audience performance 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

LinkedIn Ads: B2B advertising metrics for pipeline and attribution reporting.

ClickHouse: Columnar OLAP engine for fast aggregations.

How LinkedIn Ads entities map to ClickHouse

LinkedIn Ads entityClickHouse objectNotes
B2B campaign metricslinkedin_ads_b2b_campaign_metricsid PK · custom fields → JSON or Map columns
spendlinkedin_ads_spendid PK · linked to linkedin_ads_b2b_campaign_metrics
clickslinkedin_ads_clicksid PK · linked to linkedin_ads_b2b_campaign_metrics
leadslinkedin_ads_leadsid PK · linked to linkedin_ads_b2b_campaign_metrics

FAQ

How does Datrise handle LinkedIn Ads'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 LinkedIn Ads 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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