BambooHR → DuckDB
AI-first ETL from BambooHR into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads BambooHR into DuckDB
Datrise syncs BambooHR's employee records, org structure, lifecycle events, and workforce attributes 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
BambooHR: HRIS source for employee records and workforce analytics.
DuckDB: In-process analytics database for fast local OLAP.
How BambooHR entities map to DuckDB
| BambooHR entity | DuckDB object | Notes |
|---|---|---|
| employee records | bamboohr_employee_records | id PK · custom fields → JSON or STRUCT columns |
| org structure | bamboohr_org_structure | id PK · linked to bamboohr_employee_records |
| lifecycle events | bamboohr_lifecycle_events | TIMESTAMP WITH TIME ZONE events |
| workforce attributes | bamboohr_workforce_attributes | id PK · linked to bamboohr_employee_records |
FAQ
How does Datrise handle BambooHR'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 BambooHR 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
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