DatriseAI-first ETL

Clay to Microsoft SQL Server Integration

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

How Datrise loads Clay into Microsoft SQL Server

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists 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

Clay: Data enrichment tables that build outbound lists.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Clay entities map to Microsoft SQL Server

Clay entityMicrosoft SQL Server objectNotes
tablesclay_tablesid PK · custom fields → NVARCHAR(MAX) JSON columns
rowsclay_rowsid PK · linked to clay_tables
enrichment runsclay_enrichment_runsid PK · linked to clay_tables
waterfallsclay_waterfallsid PK · linked to clay_tables

FAQ

How does Datrise handle Clay'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 Clay 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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