DatriseAI-first ETL

Totango DuckDB

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

How Datrise loads Totango into DuckDB

Datrise syncs Totango's contacts, accounts, deals, activities, and lifecycle events 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

Totango: Customer success platform for health scores, playbooks, and renewals.

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

How Totango entities map to DuckDB

Totango entityDuckDB objectNotes
contactstotango_contactsid PK · custom fields → JSON or STRUCT columns
accountstotango_accountsid PK · linked to totango_contacts
dealstotango_dealsid PK · linked to totango_contacts
activitiestotango_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle Totango'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 Totango 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 Totango to DuckDB the easy way

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