DatriseAI-first ETL

RD Station Marketing to Mode Integration

AI-first ETL from RD Station Marketing into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads RD Station Marketing into Mode

Datrise syncs RD Station Marketing's leads, conversions, landing pages, emails, segmentations, and funnel stages into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

RD Station Marketing: Inbound marketing automation for Latin American teams.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How RD Station Marketing entities map to Mode

RD Station Marketing entityMode objectNotes
leadsrd_station_marketing_leadsid PK · custom fields → flattened columns for SQL and notebooks
conversionsrd_station_marketing_conversionsid PK · linked to rd_station_marketing_leads
landing pagesrd_station_marketing_landing_pagesid PK · linked to rd_station_marketing_leads
emailsrd_station_marketing_emailsid PK · linked to rd_station_marketing_leads

FAQ

How does Datrise handle RD Station Marketing's custom fields in Mode?

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

How does the RD Station Marketing to Mode sync stay up to date?

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

Related pipelines

Early access

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