Heroku to Microsoft SQL Server Integration
AI-first ETL from Heroku into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads Heroku into Microsoft SQL Server
Datrise syncs Heroku's apps, dynos, releases, add-ons, config vars, and build logs into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.
Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.
Ideal for Microsoft-stack analytics and Power BI Import models.
Endpoints
Heroku: Application platform with dynos and add-ons.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How Heroku entities map to Microsoft SQL Server
| Heroku entity | Microsoft SQL Server object | Notes |
|---|---|---|
| apps | heroku_apps | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| dynos | heroku_dynos | id PK · linked to heroku_apps |
| releases | heroku_releases | id PK · linked to heroku_apps |
| add-ons | heroku_add_ons | id PK · linked to heroku_apps |
FAQ
How does Datrise handle Heroku's custom fields in Microsoft SQL Server?
Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.
How does the Heroku to Microsoft SQL Server sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.
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Early access
Connect Heroku to Microsoft SQL Server the easy way
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