DatriseAI-first ETL

Polygon Stock API Snowflake

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

How Datrise loads Polygon Stock API into Snowflake

Datrise syncs Polygon Stock API's records, events, and configuration objects 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

Polygon Stock API: SaaS or API data source for analytics and warehouse sync.

Snowflake: Cloud data warehouse with separated compute and storage.

How Polygon Stock API entities map to Snowflake

Polygon Stock API entitySnowflake objectNotes
recordspolygon_stock_api_recordsid PK · custom fields → VARIANT columns
eventspolygon_stock_api_eventsTIMESTAMP_TZ events
configuration objectspolygon_stock_api_configuration_objectsid PK · linked to polygon_stock_api_records

FAQ

How does Datrise handle Polygon Stock API'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 Polygon Stock API 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.

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Early access

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