DatriseAI-first ETL

Sierra Interactive to Snowflake Integration

AI-first ETL from Sierra Interactive into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Sierra Interactive into Snowflake

Datrise syncs Sierra Interactive's leads, contacts, listings, lead scores, routing rules, and site activity 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

Sierra Interactive: Real estate websites with lead scoring and routing.

Snowflake: Cloud data warehouse with separated compute and storage.

How Sierra Interactive entities map to Snowflake

Sierra Interactive entitySnowflake objectNotes
leadssierra_interactive_leadsid PK · custom fields → VARIANT columns
contactssierra_interactive_contactsid PK · linked to sierra_interactive_leads
listingssierra_interactive_listingsid PK · linked to sierra_interactive_leads
lead scoressierra_interactive_lead_scoresid PK · linked to sierra_interactive_leads

FAQ

How does Datrise handle Sierra Interactive'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 Sierra Interactive 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

Early access

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