DatriseAI-first ETL

Follow Up Boss Snowflake

AI-first ETL from Follow Up Boss into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Follow Up Boss into Snowflake

Datrise syncs Follow Up Boss's contacts, accounts, deals, activities, and lifecycle events into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

Follow Up Boss: Real estate CRM for leads, listings, and agent follow-up.

Snowflake: Cloud data warehouse with separated compute and storage.

How Follow Up Boss entities map to Snowflake

Follow Up Boss entitySnowflake objectNotes
contactsfollow_up_boss_contactsid PK · custom fields → VARIANT columns
accountsfollow_up_boss_accountsid PK · linked to follow_up_boss_contacts
dealsfollow_up_boss_dealsid PK · linked to follow_up_boss_contacts
activitiesfollow_up_boss_activitiesTIMESTAMP_TZ events

FAQ

How does Datrise handle Follow Up Boss's custom fields in Snowflake?

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

How does the Follow Up Boss to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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