Customer.io → Microsoft SQL Server
AI-first ETL from Customer.io into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads Customer.io into Microsoft SQL Server
Datrise syncs Customer.io's profiles, segments, campaigns, deliveries, and conversion 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
Customer.io: Messaging automation based on product and behavioral data.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How Customer.io entities map to Microsoft SQL Server
| Customer.io entity | Microsoft SQL Server object | Notes |
|---|---|---|
| profiles | customer_io_profiles | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| segments | customer_io_segments | id PK · linked to customer_io_profiles |
| campaigns | customer_io_campaigns | id PK · linked to customer_io_profiles |
| deliveries | customer_io_deliveries | id PK · linked to customer_io_profiles |
FAQ
How does Datrise handle Customer.io'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 Customer.io 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
More destinations for Customer.io
- Customer.io → Oracle Database
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- Customer.io → DuckDB
- Customer.io → Amazon Athena
- Customer.io → Amazon S3 Data Lake
- Customer.io → Azure Data Lake Storage
- Customer.io → Azure Synapse
- Customer.io → Spreadsheets
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Early access
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