Retently to DuckDB Integration

How Datrise loads Retently into DuckDB

Datrise syncs Retently's surveys, responses, customers, NPS scores, campaigns, and feedback comments into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Retently: NPS and customer satisfaction survey tracking.

DuckDB: In-process analytics database for fast local OLAP.

How Retently entities map to DuckDB

Retently entity	DuckDB object	Notes
surveys	`retently_surveys`	id PK · custom fields → JSON or STRUCT columns
responses	`retently_responses`	id PK · linked to retently_surveys
customers	`retently_customers`	id PK · linked to retently_surveys
NPS scores	`retently_nps_scores`	id PK · linked to retently_surveys

FAQ

How does Datrise handle Retently's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Retently to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

Connect Retently to DuckDB the easy way

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