Lofty to Snowflake Integration
AI-first ETL from Lofty into Snowflake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Lofty into Snowflake
Datrise syncs Lofty's leads, contacts, listings, property searches, smart plans, and tour requests 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
Lofty: Real estate CRM with IDX search and AI lead nurture.
Snowflake: Cloud data warehouse with separated compute and storage.
How Lofty entities map to Snowflake
| Lofty entity | Snowflake object | Notes |
|---|---|---|
| leads | lofty_leads | id PK · custom fields → VARIANT columns |
| contacts | lofty_contacts | id PK · linked to lofty_leads |
| listings | lofty_listings | id PK · linked to lofty_leads |
| property searches | lofty_property_searches | id PK · linked to lofty_leads |
FAQ
How does Datrise handle Lofty'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 Lofty 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.
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