Salesloft → DuckDB
AI-first ETL from Salesloft into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Salesloft into DuckDB
Datrise syncs Salesloft's cadence activity, conversation signals, and revenue workflow execution 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
Salesloft: Revenue workflow platform for cadences, conversations, and coaching signals.
DuckDB: In-process analytics database for fast local OLAP.
How Salesloft entities map to DuckDB
| Salesloft entity | DuckDB object | Notes |
|---|---|---|
| cadence activity | salesloft_cadence_activity | TIMESTAMP WITH TIME ZONE events |
| conversation signals | salesloft_conversation_signals | id PK · linked to salesloft_cadence_activity |
| revenue workflow execution | salesloft_revenue_workflow_execution | id PK · linked to salesloft_cadence_activity |
FAQ
How does Datrise handle Salesloft'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 Salesloft 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
More destinations for Salesloft
Early access
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