DatriseAI-first ETL

Gong to DuckDB Integration

AI-first ETL from Gong into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Gong into DuckDB

Datrise syncs Gong's calls, transcripts, deals, users, trackers, and call topics 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

Gong: Revenue intelligence from recorded sales calls.

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

How Gong entities map to DuckDB

Gong entityDuckDB objectNotes
callsgong_callsid PK · custom fields → JSON or STRUCT columns
transcriptsgong_transcriptsid PK · linked to gong_calls
dealsgong_dealsid PK · linked to gong_calls
usersgong_usersid PK · linked to gong_calls

FAQ

How does Datrise handle Gong'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 Gong 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

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