DatriseAI-first ETL

Fastbill to Microsoft SQL Server Integration

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

How Datrise loads Fastbill into Microsoft SQL Server

Datrise syncs Fastbill's invoices, customers, line items, payments, expenses, and recurring invoices 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

Fastbill: Invoicing and accounting for small businesses.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Fastbill entities map to Microsoft SQL Server

Fastbill entityMicrosoft SQL Server objectNotes
invoicesfastbill_invoicesid PK · custom fields → NVARCHAR(MAX) JSON columns
customersfastbill_customersid PK · linked to fastbill_invoices
line itemsfastbill_line_itemsid PK · linked to fastbill_invoices
paymentsfastbill_paymentsid PK · linked to fastbill_invoices

FAQ

How does Datrise handle Fastbill'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 Fastbill 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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