Fastbill to DuckDB Integration

How Datrise loads Fastbill into DuckDB

Datrise syncs Fastbill's invoices, customers, line items, payments, expenses, and recurring invoices 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

Fastbill: Invoicing and accounting for small businesses.

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

How Fastbill entities map to DuckDB

Fastbill entity	DuckDB object	Notes
invoices	`fastbill_invoices`	id PK · custom fields → JSON or STRUCT columns
customers	`fastbill_customers`	id PK · linked to fastbill_invoices
line items	`fastbill_line_items`	id PK · linked to fastbill_invoices
payments	`fastbill_payments`	id PK · linked to fastbill_invoices

FAQ

How does Datrise handle Fastbill'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 Fastbill 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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