CSV File to PostgreSQL Integration

How Datrise loads CSV File into PostgreSQL

Datrise syncs CSV File's rows, columns, headers, delimiters, file batches, and encodings 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

CSV File: Delimited flat files from exports and drops.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How CSV File entities map to PostgreSQL

CSV File entity	PostgreSQL object	Notes
rows	`csv_file_rows`	id PK · custom fields → jsonb columns
columns	`csv_file_columns`	id PK · linked to csv_file_rows
headers	`csv_file_headers`	id PK · linked to csv_file_rows
delimiters	`csv_file_delimiters`	id PK · linked to csv_file_rows

FAQ

How does Datrise handle CSV File'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 CSV File 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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