DatriseAI-first ETL

Exchange Rates API to Mode Integration

AI-first ETL from Exchange Rates API into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Exchange Rates API into Mode

Datrise syncs Exchange Rates API's exchange rates, currency pairs, base currencies, rate dates, and historical rates into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Exchange Rates API: Foreign exchange reference rates by currency pair.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Exchange Rates API entities map to Mode

Exchange Rates API entityMode objectNotes
exchange ratesexchange_rates_api_exchange_ratestemporal columns events
currency pairsexchange_rates_api_currency_pairsid PK · linked to exchange_rates_api_exchange_rates
base currenciesexchange_rates_api_base_currenciesid PK · linked to exchange_rates_api_exchange_rates
rate datesexchange_rates_api_rate_datesid PK · linked to exchange_rates_api_exchange_rates

FAQ

How does Datrise handle Exchange Rates API's custom fields in Mode?

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

How does the Exchange Rates API to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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