DatriseAI-first ETL

My Hours Neon

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

How Datrise loads My Hours into Neon

Datrise syncs My Hours'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

My Hours: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How My Hours entities map to Neon

My Hours entityNeon objectNotes
recordsmy_hours_recordsid PK · custom fields → jsonb columns
eventsmy_hours_eventstimestamptz events
configuration objectsmy_hours_configuration_objectsid PK · linked to my_hours_records

FAQ

How does Datrise handle My Hours'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 My Hours 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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