Workday → DuckDB
AI-first ETL from Workday into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Workday into DuckDB
Datrise syncs Workday's HR, finance entities, organizational structures, and operational events 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
Workday: Enterprise HR and finance source for operational reporting.
DuckDB: In-process analytics database for fast local OLAP.
How Workday entities map to DuckDB
| Workday entity | DuckDB object | Notes |
|---|---|---|
| HR | workday_hr | id PK · custom fields → JSON or STRUCT columns |
| finance entities | workday_finance_entities | id PK · linked to workday_hr |
| organizational structures | workday_organizational_structures | id PK · linked to workday_hr |
| operational events | workday_operational_events | TIMESTAMP WITH TIME ZONE events |
FAQ
How does Datrise handle Workday'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 Workday 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 Workday
Early access
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