DatriseAI-first ETL

Tvmaze Schedule Neon

AI-first ETL from Tvmaze Schedule into Neon. Governed entities, incremental sync, typed landing tables.

How Datrise loads Tvmaze Schedule into Neon

Datrise syncs Tvmaze Schedule's records, events, and configuration objects into Neon 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 updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

Tvmaze Schedule: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How Tvmaze Schedule entities map to Neon

Tvmaze Schedule entityNeon objectNotes
recordstvmaze_schedule_recordsid PK · custom fields → jsonb columns
eventstvmaze_schedule_eventstimestamptz events
configuration objectstvmaze_schedule_configuration_objectsid PK · linked to tvmaze_schedule_records

FAQ

How does Datrise handle Tvmaze Schedule's custom fields in Neon?

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 Neon types.

How does the Tvmaze Schedule to Neon sync stay up to date?

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

Related pipelines

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