DatriseAI-first ETL

Xero Databricks SQL Warehouse

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

How Datrise loads Xero into Databricks SQL Warehouse

Datrise syncs Xero's contacts, invoices, bank transactions, accounts, and payments into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Xero: Cloud accounting for SMB ledgers and cash flow.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Xero entities map to Databricks SQL Warehouse

Xero entityDatabricks SQL Warehouse objectNotes
contactsxero_contactsid PK · custom fields → VARIANT 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 Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Xero to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

Early access

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