DatriseAI-first ETL

The Guardian API to Snowflake Integration

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

How Datrise loads The Guardian API into Snowflake

Datrise syncs The Guardian API's articles, sections, tags, contributors, publication dates, and headlines 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

The Guardian API: Guardian article archive and section metadata.

Snowflake: Cloud data warehouse with separated compute and storage.

How The Guardian API entities map to Snowflake

The Guardian API entitySnowflake objectNotes
articlesthe_guardian_api_articlesid PK · custom fields → VARIANT columns
sectionsthe_guardian_api_sectionsid PK · linked to the_guardian_api_articles
tagsthe_guardian_api_tagsid PK · linked to the_guardian_api_articles
contributorsthe_guardian_api_contributorsid PK · linked to the_guardian_api_articles

FAQ

How does Datrise handle The Guardian 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 The Guardian 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.

Related pipelines

Early access

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