Plaid → PostgreSQL
AI-first ETL from Plaid into PostgreSQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Plaid into PostgreSQL
Datrise syncs Plaid's records, events, and configuration objects into PostgreSQL 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 each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.
Ideal for operational analytics and application backends that need fresh, queryable copies of your data.
Endpoints
Plaid: SaaS or API data source for analytics and warehouse sync.
PostgreSQL: Open-source relational database with strong SQL and extensions.
How Plaid entities map to PostgreSQL
| Plaid entity | PostgreSQL object | Notes |
|---|---|---|
| records | plaid_records | id PK · custom fields → jsonb columns |
| events | plaid_events | timestamptz events |
| configuration objects | plaid_configuration_objects | id PK · linked to plaid_records |
FAQ
How does Datrise handle Plaid's custom fields in PostgreSQL?
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 PostgreSQL types.
How does the Plaid to PostgreSQL sync stay up to date?
It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
Related pipelines
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Early access
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