DatriseAI-first ETL

SuiteCRM DuckDB

AI-first ETL from SuiteCRM into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads SuiteCRM into DuckDB

Datrise syncs SuiteCRM's open-source CRM entities, custom modules, and configurable 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

SuiteCRM: Open-source CRM for customizable sales and customer operations.

DuckDB: In-process analytics database for fast local OLAP.

How SuiteCRM entities map to DuckDB

SuiteCRM entityDuckDB objectNotes
open-source CRM entitiessuitecrm_open_source_crm_entitiesid PK · custom fields → JSON or STRUCT columns
custom modulessuitecrm_custom_modulesid PK · linked to suitecrm_open_source_crm_entities
configurable workflowssuitecrm_configurable_workflowsid PK · linked to suitecrm_open_source_crm_entities

FAQ

How does Datrise handle SuiteCRM'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 SuiteCRM to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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