DatriseAI-first ETL

HighLevel Snowflake

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

How Datrise loads HighLevel into Snowflake

Datrise syncs HighLevel's agency CRM records, funnels, opportunities, and messaging workflows 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

HighLevel: Agency-focused CRM for leads, funnels, and customer messaging.

Snowflake: Cloud data warehouse with separated compute and storage.

How HighLevel entities map to Snowflake

HighLevel entitySnowflake objectNotes
agency CRM recordshighlevel_agency_crm_recordsid PK · custom fields → VARIANT columns
funnelshighlevel_funnelsid PK · linked to highlevel_agency_crm_records
opportunitieshighlevel_opportunitiesid PK · linked to highlevel_agency_crm_records
messaging workflowshighlevel_messaging_workflowsid PK · linked to highlevel_agency_crm_records

FAQ

How does Datrise handle HighLevel'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 HighLevel 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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