DatriseAI-first ETL

Paystack to Amazon QuickSight Integration

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

How Datrise loads Paystack into Amazon QuickSight

Datrise syncs Paystack's transactions, customers, plans, subscriptions, settlements, and refunds into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Paystack: Online payment collection for African markets.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Paystack entities map to Amazon QuickSight

Paystack entityAmazon QuickSight objectNotes
transactionspaystack_transactionsid PK · custom fields → flattened columns for analyses
customerspaystack_customersid PK · linked to paystack_transactions
planspaystack_plansid PK · linked to paystack_transactions
subscriptionspaystack_subscriptionsid PK · linked to paystack_transactions

FAQ

How does Datrise handle Paystack's custom fields in Amazon QuickSight?

Flexible values are stored as flattened columns for analyses, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon QuickSight types.

How does the Paystack to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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