HighLevel → DuckDB
AI-first ETL from HighLevel into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads HighLevel into DuckDB
Datrise syncs HighLevel's agency CRM records, funnels, opportunities, and messaging workflows into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.
Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.
Ideal for local and notebook analytics without standing up a server.
Endpoints
HighLevel: Agency-focused CRM for leads, funnels, and customer messaging.
DuckDB: In-process analytics database for fast local OLAP.
How HighLevel entities map to DuckDB
| HighLevel entity | DuckDB object | Notes |
|---|---|---|
| agency CRM records | highlevel_agency_crm_records | id PK · custom fields → JSON or STRUCT columns |
| funnels | highlevel_funnels | id PK · linked to highlevel_agency_crm_records |
| opportunities | highlevel_opportunities | id PK · linked to highlevel_agency_crm_records |
| messaging workflows | highlevel_messaging_workflows | id PK · linked to highlevel_agency_crm_records |
FAQ
How does Datrise handle HighLevel's custom fields in DuckDB?
Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.
How does the HighLevel to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
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