DatriseAI-first ETL

CoinMarketCap to Snowflake Integration

AI-first ETL from CoinMarketCap into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads CoinMarketCap into Snowflake

Datrise syncs CoinMarketCap's cryptocurrencies, quotes, market caps, trading volumes, exchange listings, and rankings into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

CoinMarketCap: Crypto asset rankings, quotes, and market caps.

Snowflake: Cloud data warehouse with separated compute and storage.

How CoinMarketCap entities map to Snowflake

CoinMarketCap entitySnowflake objectNotes
cryptocurrenciescoinmarketcap_cryptocurrenciesid PK · custom fields → VARIANT columns
quotescoinmarketcap_quotesid PK · linked to coinmarketcap_cryptocurrencies
market capscoinmarketcap_market_capsid PK · linked to coinmarketcap_cryptocurrencies
trading volumescoinmarketcap_trading_volumesid PK · linked to coinmarketcap_cryptocurrencies

FAQ

How does Datrise handle CoinMarketCap's custom fields in Snowflake?

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

How does the CoinMarketCap to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

Early access

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