DatriseAI-first ETL

Openweather to PostgreSQL Integration

AI-first ETL from Openweather into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Openweather into PostgreSQL

Datrise syncs Openweather's current conditions, forecasts, locations, temperature readings, precipitation, and observation times into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Openweather: Current conditions and weather forecast data.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Openweather entities map to PostgreSQL

Openweather entityPostgreSQL objectNotes
current conditionsopenweather_current_conditionsid PK · custom fields → jsonb columns
forecastsopenweather_forecastsid PK · linked to openweather_current_conditions
locationsopenweather_locationsid PK · linked to openweather_current_conditions
temperature readingsopenweather_temperature_readingsid PK · linked to openweather_current_conditions

FAQ

How does Datrise handle Openweather's custom fields in PostgreSQL?

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

How does the Openweather to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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