DatriseAI-first ETL

ConfigCat to Neon Integration

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

How Datrise loads ConfigCat into Neon

Datrise syncs ConfigCat's feature flags, settings, environments, config values, evaluations, and targeting rules 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

ConfigCat: Feature flag and remote configuration service.

Neon: Serverless Postgres destination with branching and autoscaling.

How ConfigCat entities map to Neon

ConfigCat entityNeon objectNotes
feature flagsconfigcat_feature_flagsid PK · custom fields → jsonb columns
settingsconfigcat_settingsid PK · linked to configcat_feature_flags
environmentsconfigcat_environmentsid PK · linked to configcat_feature_flags
config valuesconfigcat_config_valuesid PK · linked to configcat_feature_flags

FAQ

How does Datrise handle ConfigCat'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 ConfigCat 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

Early access

Connect ConfigCat 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.