Exchange Rates API to Google BigQuery Integration
AI-first ETL from Exchange Rates API into Google BigQuery. Governed entities, incremental sync, typed landing tables.
How Datrise loads Exchange Rates API into Google BigQuery
Datrise syncs Exchange Rates API's exchange rates, currency pairs, base currencies, rate dates, and historical rates into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.
Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.
Ideal for Google-stack analytics and ML on serverless infrastructure.
Endpoints
Exchange Rates API: Foreign exchange reference rates by currency pair.
Google BigQuery: Serverless analytics warehouse on GCP.
How Exchange Rates API entities map to Google BigQuery
| Exchange Rates API entity | Google BigQuery object | Notes |
|---|---|---|
| exchange rates | exchange_rates_api_exchange_rates | TIMESTAMP events |
| currency pairs | exchange_rates_api_currency_pairs | id PK · linked to exchange_rates_api_exchange_rates |
| base currencies | exchange_rates_api_base_currencies | id PK · linked to exchange_rates_api_exchange_rates |
| rate dates | exchange_rates_api_rate_dates | id PK · linked to exchange_rates_api_exchange_rates |
FAQ
How does Datrise handle Exchange Rates API's custom fields in Google BigQuery?
Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.
How does the Exchange Rates API to Google BigQuery sync stay up to date?
It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.
Related pipelines
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Early access
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