Pendo → DuckDB
AI-first ETL from Pendo into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Pendo into DuckDB
Datrise syncs Pendo's events, guides, NPS, feature adoption, and account metadata 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
Pendo: Product analytics and in-app guidance for SaaS teams.
DuckDB: In-process analytics database for fast local OLAP.
How Pendo entities map to DuckDB
| Pendo entity | DuckDB object | Notes |
|---|---|---|
| events | pendo_events | TIMESTAMP WITH TIME ZONE events |
| guides | pendo_guides | id PK · linked to pendo_events |
| NPS | pendo_nps | id PK · linked to pendo_events |
| feature adoption | pendo_feature_adoption | id PK · linked to pendo_events |
FAQ
How does Datrise handle Pendo'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 Pendo to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
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Early access
Connect Pendo to DuckDB the easy way
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