DatriseAI-first ETL

Mssql SQL Server PlanetScale

AI-first ETL from Mssql SQL Server into PlanetScale. Governed entities, incremental sync, typed landing tables.

How Datrise loads Mssql SQL Server into PlanetScale

Datrise syncs Mssql SQL Server's records, events, and configuration objects into PlanetScale as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Vitess sharding by tenant or entity key for very large tables. PlanetScale disallows foreign-key constraints by default, so Datrise models relationships by stable id columns rather than enforced FKs.

Ideal for horizontally scalable MySQL apps on Vitess.

Endpoints

Mssql SQL Server: SaaS or API data source for analytics and warehouse sync.

PlanetScale: Serverless MySQL platform with safe schema workflows.

How Mssql SQL Server entities map to PlanetScale

Mssql SQL Server entityPlanetScale objectNotes
recordsmssql_sql_server_recordsid PK · custom fields → JSON columns
eventsmssql_sql_server_eventsDATETIME events
configuration objectsmssql_sql_server_configuration_objectsid PK · linked to mssql_sql_server_records

FAQ

How does Datrise handle Mssql SQL Server's custom fields in PlanetScale?

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

How does the Mssql SQL Server to PlanetScale sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

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