DatriseAI-first ETL

Public API to Microsoft SQL Server Integration

AI-first ETL from Public API into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Public API into Microsoft SQL Server

Datrise syncs Public API's records, response payloads, pagination cursors, request parameters, schemas, and fetch timestamps 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

Public API: Generic REST endpoint pulled on a schedule.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Public API entities map to Microsoft SQL Server

Public API entityMicrosoft SQL Server objectNotes
recordspublic_api_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
response payloadspublic_api_response_payloadsid PK · linked to public_api_records
pagination cursorspublic_api_pagination_cursorsid PK · linked to public_api_records
request parameterspublic_api_request_parametersid PK · linked to public_api_records

FAQ

How does Datrise handle Public API'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 Public API to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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