Short.io to DuckDB Integration
AI-first ETL from Short.io into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Short.io into DuckDB
Datrise syncs Short.io's links, domains, clicks, referrers, countries, and link tags 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
Short.io: Branded short links and click analytics.
DuckDB: In-process analytics database for fast local OLAP.
How Short.io entities map to DuckDB
| Short.io entity | DuckDB object | Notes |
|---|---|---|
| links | short_io_links | id PK · custom fields → JSON or STRUCT columns |
| domains | short_io_domains | id PK · linked to short_io_links |
| clicks | short_io_clicks | id PK · linked to short_io_links |
| referrers | short_io_referrers | id PK · linked to short_io_links |
FAQ
How does Datrise handle Short.io'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 Short.io 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 Short.io
Early access
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