DatriseAI-first ETL

GitHub Redash

AI-first ETL from GitHub into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads GitHub into Redash

Datrise syncs GitHub's repositories, issues, pull requests, commits, and workflow runs into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

GitHub: Developer platform for repos, issues, and delivery workflows.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How GitHub entities map to Redash

GitHub entityRedash objectNotes
repositoriesgithub_repositoriesid PK · custom fields → flattened columns for query results
issuesgithub_issuesid PK · linked to github_repositories
pull requestsgithub_pull_requestsid PK · linked to github_repositories
commitsgithub_commitsid PK · linked to github_repositories

FAQ

How does Datrise handle GitHub's custom fields in Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the GitHub to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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