DatriseAI-first ETL

Omie CRM to Databricks SQL Warehouse Integration

AI-first ETL from Omie CRM into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Omie CRM into Databricks SQL Warehouse

Datrise syncs Omie CRM's clients, opportunities, sales orders, invoices, products, and accounts receivable into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Omie CRM: Brazilian ERP and CRM for SMB sales and finance.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Omie CRM entities map to Databricks SQL Warehouse

Omie CRM entityDatabricks SQL Warehouse objectNotes
clientsomie_clientsid PK · custom fields → VARIANT or STRUCT columns
opportunitiesomie_opportunitiesid PK · linked to omie_clients
sales ordersomie_sales_ordersid PK · linked to omie_clients
invoicesomie_invoicesid PK · linked to omie_clients

FAQ

How does Datrise handle Omie CRM's custom fields in Databricks SQL Warehouse?

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

How does the Omie CRM to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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