DatriseAI-first ETL

Apollo Microsoft SQL Server

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

How Datrise loads Apollo into Microsoft SQL Server

Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity 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

Apollo: Sales intelligence and engagement platform with account-level activity.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Apollo entities map to Microsoft SQL Server

Apollo entityMicrosoft SQL Server objectNotes
sales intelligence recordsapollo_sales_intelligence_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
account engagementapollo_account_engagementid PK · linked to apollo_sales_intelligence_records
outbound activityapollo_outbound_activitydatetime2 events

FAQ

How does Datrise handle Apollo'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 Apollo 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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