GoCardless to Amazon Athena Integration

How Datrise loads GoCardless into Amazon Athena

Datrise syncs GoCardless's payments, customers, mandates, subscriptions, payouts, and refunds 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

GoCardless: Bank debit collection and recurring payments.

Amazon Athena: Serverless SQL over S3 data lake tables.

How GoCardless entities map to Amazon Athena

GoCardless entity	Amazon Athena object	Notes
payments	`gocardless_payments`	id PK · custom fields → struct/map columns in Parquet
customers	`gocardless_customers`	id PK · linked to gocardless_payments
mandates	`gocardless_mandates`	id PK · linked to gocardless_payments
subscriptions	`gocardless_subscriptions`	id PK · linked to gocardless_payments

FAQ

How does Datrise handle GoCardless'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 GoCardless 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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