DatriseAI-first ETL

Xero DuckDB

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

How Datrise loads Xero into DuckDB

Datrise syncs Xero's contacts, invoices, bank transactions, accounts, and payments 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

Xero: Cloud accounting for SMB ledgers and cash flow.

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

How Xero entities map to DuckDB

Xero entityDuckDB objectNotes
contactsxero_contactsid PK · custom fields → JSON or STRUCT columns
invoicesxero_invoicesid PK · linked to xero_contacts
bank transactionsxero_bank_transactionsid PK · linked to xero_contacts
accountsxero_accountsid PK · linked to xero_contacts

FAQ

How does Datrise handle Xero'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 Xero 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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