DatriseAI-first ETL

Creatio Databricks SQL Warehouse

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

How Datrise loads Creatio into Databricks SQL Warehouse

Datrise syncs Creatio's no-code CRM processes, entities, and cross-team workflow orchestration 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

Creatio: No-code CRM and process automation platform for enterprise teams.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Creatio entities map to Databricks SQL Warehouse

Creatio entityDatabricks SQL Warehouse objectNotes
no-code CRM processescreatio_no_code_crm_processesid PK · custom fields → VARIANT or STRUCT columns
entitiescreatio_entitiesid PK · linked to creatio_no_code_crm_processes
cross-team workflow orchestrationcreatio_cross_team_workflow_orchestrationid PK · linked to creatio_no_code_crm_processes

FAQ

How does Datrise handle Creatio'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 Creatio 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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