Bronto → DuckDB
AI-first ETL from Bronto into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Bronto into DuckDB
Datrise syncs Bronto's records, events, and configuration objects 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
Bronto: SaaS or API data source for analytics and warehouse sync.
DuckDB: In-process analytics database for fast local OLAP.
How Bronto entities map to DuckDB
| Bronto entity | DuckDB object | Notes |
|---|---|---|
| records | bronto_records | id PK · custom fields → JSON or STRUCT columns |
| events | bronto_events | TIMESTAMP WITH TIME ZONE events |
| configuration objects | bronto_configuration_objects | id PK · linked to bronto_records |
FAQ
How does Datrise handle Bronto'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 Bronto 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 Bronto
Early access
Connect Bronto to DuckDB the easy way
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