DatriseAI-first ETL

Referral Saasquatch to Mode Integration

AI-first ETL from Referral Saasquatch into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Referral Saasquatch into Mode

Datrise syncs Referral Saasquatch's users, referrals, rewards, programs, redemptions, and account balances 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

Referral Saasquatch: Referral and loyalty program tracking.

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

How Referral Saasquatch entities map to Mode

Referral Saasquatch entityMode objectNotes
usersreferral_saasquatch_usersid PK · custom fields → flattened columns for SQL and notebooks
referralsreferral_saasquatch_referralsid PK · linked to referral_saasquatch_users
rewardsreferral_saasquatch_rewardsid PK · linked to referral_saasquatch_users
programsreferral_saasquatch_programsid PK · linked to referral_saasquatch_users

FAQ

How does Datrise handle Referral Saasquatch'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 Referral Saasquatch 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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