CoinAPI to Qlik Integration
AI-first ETL from CoinAPI into Qlik. Governed entities, incremental sync, typed landing tables.
How Datrise loads CoinAPI into Qlik
Datrise syncs CoinAPI's exchange rates, symbols, trades, order book snapshots, OHLCV bars, and exchanges into Qlik as tables loaded into Qlik's associative engine (often via QVD). Flexible or custom fields land in flattened columns for the data model, and timestamps such as created, updated, and status changes are typed as date/time fields.
Sync is incremental: Datrise uses incremental QVD loads merged on stable id, so re-runs update only what changed. QVD files per entity and load date. Qlik's associative model joins on identically named fields, so Datrise standardizes key names so associations link correctly.
Ideal for associative, in-memory exploration in Qlik Sense.
Endpoints
CoinAPI: Consolidated crypto market data API.
Qlik: Associative analytics with Qlik Sense apps and governed data models.
How CoinAPI entities map to Qlik
| CoinAPI entity | Qlik object | Notes |
|---|---|---|
| exchange rates | coin_api_exchange_rates | date/time fields events |
| symbols | coin_api_symbols | id PK · linked to coin_api_exchange_rates |
| trades | coin_api_trades | id PK · linked to coin_api_exchange_rates |
| order book snapshots | coin_api_order_book_snapshots | id PK · linked to coin_api_exchange_rates |
FAQ
How does Datrise handle CoinAPI's custom fields in Qlik?
Flexible values are stored as flattened columns for the data model, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Qlik types.
How does the CoinAPI to Qlik sync stay up to date?
It runs incrementally — Datrise uses incremental QVD loads merged on stable id.
Related pipelines
More destinations for CoinAPI
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