GitHub → DuckDB
AI-first ETL from GitHub into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads GitHub into DuckDB
Datrise syncs GitHub's repositories, issues, pull requests, commits, and workflow runs 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
GitHub: Developer platform for repos, issues, and delivery workflows.
DuckDB: In-process analytics database for fast local OLAP.
How GitHub entities map to DuckDB
| GitHub entity | DuckDB object | Notes |
|---|---|---|
| repositories | github_repositories | id PK · custom fields → JSON or STRUCT columns |
| issues | github_issues | id PK · linked to github_repositories |
| pull requests | github_pull_requests | id PK · linked to github_repositories |
| commits | github_commits | id PK · linked to github_repositories |
FAQ
How does Datrise handle GitHub'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 GitHub 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
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Early access
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