BoomTown → Neon
AI-first ETL from BoomTown into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads BoomTown into Neon
Datrise syncs BoomTown's contacts, accounts, deals, activities, and lifecycle events 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
BoomTown: Real estate CRM for leads, listings, and agent follow-up.
Neon: Serverless Postgres destination with branching and autoscaling.
How BoomTown entities map to Neon
| BoomTown entity | Neon object | Notes |
|---|---|---|
| contacts | boomtown_contacts | id PK · custom fields → jsonb columns |
| accounts | boomtown_accounts | id PK · linked to boomtown_contacts |
| deals | boomtown_deals | id PK · linked to boomtown_contacts |
| activities | boomtown_activities | timestamptz events |
FAQ
How does Datrise handle BoomTown'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 BoomTown 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 BoomTown
Early access
Connect BoomTown to Neon the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.