Convex Dev → Neon
AI-first ETL from Convex Dev into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads Convex Dev into Neon
Datrise syncs Convex Dev'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
Convex Dev: SaaS or API data source for analytics and warehouse sync.
Neon: Serverless Postgres destination with branching and autoscaling.
How Convex Dev entities map to Neon
| Convex Dev entity | Neon object | Notes |
|---|---|---|
| records | convex_dev_records | id PK · custom fields → jsonb columns |
| events | convex_dev_events | timestamptz events |
| configuration objects | convex_dev_configuration_objects | id PK · linked to convex_dev_records |
FAQ
How does Datrise handle Convex Dev'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 Convex Dev 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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