SugarCRM → DuckDB
AI-first ETL from SugarCRM into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads SugarCRM into DuckDB
Datrise syncs SugarCRM's enterprise account, opportunity, and customer-service intelligence data 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
SugarCRM: Enterprise CRM platform for sales, service, and account intelligence.
DuckDB: In-process analytics database for fast local OLAP.
How SugarCRM entities map to DuckDB
| SugarCRM entity | DuckDB object | Notes |
|---|---|---|
| enterprise account | sugarcrm_enterprise_account | id PK · custom fields → JSON or STRUCT columns |
| opportunity | sugarcrm_opportunity | id PK · linked to sugarcrm_enterprise_account |
| customer-service intelligence data | sugarcrm_customer_service_intelligence_data | id PK · linked to sugarcrm_enterprise_account |
FAQ
How does Datrise handle SugarCRM'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 SugarCRM 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
More destinations for SugarCRM
Early access
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