PipeRun to Neon Integration
AI-first ETL from PipeRun into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads PipeRun into Neon
Datrise syncs PipeRun's deals, contacts, companies, pipeline stages, activities, and sales teams 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
PipeRun: Sales pipeline management for Brazilian revenue teams.
Neon: Serverless Postgres destination with branching and autoscaling.
How PipeRun entities map to Neon
| PipeRun entity | Neon object | Notes |
|---|---|---|
| deals | piperun_deals | id PK · custom fields → jsonb columns |
| contacts | piperun_contacts | id PK · linked to piperun_deals |
| companies | piperun_companies | id PK · linked to piperun_deals |
| pipeline stages | piperun_pipeline_stages | id PK · linked to piperun_deals |
FAQ
How does Datrise handle PipeRun'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 PipeRun 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
More destinations for PipeRun
Early access
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