DatriseAI-first ETL

Xero Amazon Athena

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

How Datrise loads Xero into Amazon Athena

Datrise syncs Xero's contacts, invoices, bank transactions, accounts, and payments into Amazon Athena as partitioned Parquet in S3 exposed as an Athena table. Flexible or custom fields land in struct/map columns in Parquet, and timestamps such as created, updated, and status changes are typed as timestamp.

Sync is incremental: Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog, so re-runs update only what changed. Hive-style partitioning by load date so Athena scans only new data. Athena bills per byte scanned and small files hurt, so Datrise compacts to right-sized Parquet rather than many tiny objects.

Ideal for serverless SQL over an S3 lake without a running warehouse.

Endpoints

Xero: Cloud accounting for SMB ledgers and cash flow.

Amazon Athena: Serverless SQL over S3 data lake tables.

How Xero entities map to Amazon Athena

Xero entityAmazon Athena objectNotes
contactsxero_contactsid PK · custom fields → struct/map columns in Parquet
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 Amazon Athena?

Flexible values are stored as struct/map columns in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Athena types.

How does the Xero to Amazon Athena sync stay up to date?

It runs incrementally — Datrise uses writes new Parquet partitions and registers them in the Glue Data Catalog.

Related pipelines

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