DatriseAI-first ETL

EngageBay Microsoft SQL Server

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

How Datrise loads EngageBay into Microsoft SQL Server

Datrise syncs EngageBay's contacts, accounts, deals, activities, and lifecycle events 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

EngageBay: CRM for SMB teams managing pipeline, contacts, and customer activity.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How EngageBay entities map to Microsoft SQL Server

EngageBay entityMicrosoft SQL Server objectNotes
contactsengagebay_contactsid PK · custom fields → NVARCHAR(MAX) JSON columns
accountsengagebay_accountsid PK · linked to engagebay_contacts
dealsengagebay_dealsid PK · linked to engagebay_contacts
activitiesengagebay_activitiesdatetime2 events

FAQ

How does Datrise handle EngageBay'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 EngageBay 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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