Google Ecommerce to Microsoft SQL Server Integration
AI-first ETL from Google Ecommerce into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Ecommerce into Microsoft SQL Server
Datrise syncs Google Ecommerce's transactions, products, product impressions, checkout steps, revenue, and refunds 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
Google Ecommerce: Ecommerce reporting from Google Analytics.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How Google Ecommerce entities map to Microsoft SQL Server
| Google Ecommerce entity | Microsoft SQL Server object | Notes |
|---|---|---|
| transactions | google_ecommerce_transactions | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| products | google_ecommerce_products | id PK · linked to google_ecommerce_transactions |
| product impressions | google_ecommerce_product_impressions | id PK · linked to google_ecommerce_transactions |
| checkout steps | google_ecommerce_checkout_steps | id PK · linked to google_ecommerce_transactions |
FAQ
How does Datrise handle Google Ecommerce'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 Google Ecommerce 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 Google Ecommerce
- Google Ecommerce → Oracle Database
- Google Ecommerce → Snowflake
- Google Ecommerce → Google BigQuery
- Google Ecommerce → Amazon Redshift
- Google Ecommerce → Databricks SQL Warehouse
- Google Ecommerce → ClickHouse
- Google Ecommerce → DuckDB
- Google Ecommerce → Amazon Athena
- Google Ecommerce → Amazon S3 Data Lake
- Google Ecommerce → Azure Data Lake Storage
- Google Ecommerce → Azure Synapse
- Google Ecommerce → Spreadsheets
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- Import API → Microsoft SQL Server
Early access
Connect Google Ecommerce to Microsoft SQL Server the easy way
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