DatriseAI-first ETL

Microsoft Dynamics 365 DuckDB

AI-first ETL from Microsoft Dynamics 365 into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Microsoft Dynamics 365 into DuckDB

Datrise syncs Microsoft Dynamics 365's accounts, opportunities, activities, and enterprise CRM process 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

Microsoft Dynamics 365: Microsoft enterprise CRM and ERP suite.

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

How Microsoft Dynamics 365 entities map to DuckDB

Microsoft Dynamics 365 entityDuckDB objectNotes
accountsmicrosoft_dynamics_accountsid PK · custom fields → JSON or STRUCT columns
opportunitiesmicrosoft_dynamics_opportunitiesid PK · linked to microsoft_dynamics_accounts
activitiesmicrosoft_dynamics_activitiesTIMESTAMP WITH TIME ZONE events
enterprise CRM process datamicrosoft_dynamics_enterprise_crm_process_dataid PK · linked to microsoft_dynamics_accounts

FAQ

How does Datrise handle Microsoft Dynamics 365'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 Microsoft Dynamics 365 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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