Create a Sync from MSSQL to Batch Profile Attributes

Before you start

To create an MSSQL → Batch sync, you'll need:

  • Access to the Batch dashboard

  • An MSSQL-compatible database (Azure SQL Database, Azure SQL Managed Instance, Microsoft Fabric Warehouse, or SQL Server 2012+) containing one row per profile

  • Credentials to connect: either a username/password or a Microsoft Entra ID service principal (Client ID + Client Secret)

  • A table (or view) that follows the Cloud Sync input format (see below)


1) Prepare your MSSQL table

Cloud Sync expects your MSSQL source (table or view) to include:

  1. A profile identifier (to know which profile to update)

  2. A cursor field (to know what changed since the last run)

  3. Any number of attribute columns (sent to Batch as profile attributes)


1.1 One row per profile

Your source must contain one row per profile. Each row is interpreted as an update to a single Batch profile.


1.2 Required columns

Your table (or view) must include:

Column
Required
Description

custom_id

The profile identifier in Batch

last_updated_at

Cursor used for incremental sync

Important: last_updated_at must be updated every time any synced attribute changes, otherwise updates may not be picked up by the next run.


1.3 Attribute naming rules

Cloud Sync reads your MSSQL columns and converts them into Batch profile attributes.

Because the Batch Profile API uses characters like $, (, or ) that are not valid in SQL column names, Cloud Sync relies on prefixes in column names to represent typed or native fields.

Supported prefixes

Prefix
Meaning
Example

date__

Date attribute

date__birthday

url__

URL attribute

url__avatar

batch__

Native profile fields (instead of $...)

batch__email_address


1.4 Example schema (e-commerce)

Here's a table format you can use as a reference:

How this maps in Batch:

  • custom_id identifies the profile

  • batch__email_address updates the profile's native email field

  • plan, country, lifetime_value, is_vip become attributes

  • url__avatar is interpreted as a URL attribute

  • date__birthday and date__last_purchase are interpreted as date attributes


1.5 Using a View

If your raw table doesn't match the expected naming or format, create an MSSQL View that converts your schema into the correct conventions.

Example:

This approach lets you:

  • rename fields with the correct prefixes (batch__, date__, url__)

  • compute a reliable last_updated_at

  • ensure you always expose one row per profile


1.6 Handling nulls

If a column value is NULL, Batch interprets it as attribute removal for that profile.

If you don't want an attribute removed:

  • ensure your view returns a non-null value, or

  • exclude the column from the sync entirely.


1.7 Attributes limits and constraints

When syncing data from MSSQL to Batch, all attributes sent through Cloud Sync must respect the same limits and constraints as the Batch Profile API. See Profile API documentation, the attributes object.


2) Set up database access

Batch connects to your MSSQL database using either username/password or Microsoft Entra ID (recommended for Azure SQL).

Option A — Username / Password

Create a dedicated read-only user in your database and grant it SELECT access on the relevant table or view:

This method uses a service principal (App Registration) to authenticate without storing a password.

2.1 Create an App Registration in Entra ID

  1. Navigate to Entra ID → App registrations → New registration

  2. Give it a name (e.g. Batch Cloud Sync) and register it

  3. Note the Application (Client) ID — you'll need it later

  4. Go to Certificates & secrets → New client secret

  5. Note the Value of the client secret — it is only shown once

2.2 Create a database user for the service principal

In your Azure SQL Database, run the following as an admin:


3) Create the Sync in the Batch dashboard

Cloud Sync is configured from the dashboard via a dedicated Sync module.

  1. Open the Batch dashboard

  2. Go to Data → Cloud Sync

  3. Click Create Sync

  4. Select MSSQL as the source


3.1 Configure your MSSQL connection

Enter:

  • Host — your server hostname (e.g. myserver.database.windows.net for Azure SQL, or <workspace>.datawarehouse.fabric.microsoft.com for Microsoft Fabric Warehouse)

  • Port — default is 1433

  • Database — the name of your database

  • Schema — the schema containing your table or view

  • Table or View — the name of the source table or view

Then fill in your credentials:

  • Username / Password if using SQL authentication, or

  • Entra ID Client ID and Entra ID Client Secret if using Microsoft Entra ID

Batch validates the connection before continuing.


3.2 Configure profile mapping

Cloud Sync applies a simple mapping model:

  • custom_id → identifies which Batch profile to update

  • last_updated_at → used only for incremental sync logic

  • all other columns → mapped to profile attributes


4) How incremental sync works

Cloud Sync uses incremental processing, which means it does not re-import your full dataset at every run. Instead, it fetches only the rows that changed since the last successful sync.


4.1 The last_updated_at cursor

Batch stores the last successful cursor value internally.

At each run, Batch fetches only rows where:

  • last_updated_at is greater than the last stored cursor

This makes sync runs faster, more scalable, and more cost-efficient.


4.2 Inserts, updates, and deletes

Incremental syncs naturally capture:

  • ✅ inserts

  • ✅ updates

They do not automatically capture:

  • ❌ deletes

If you need deletions reflected in Batch, implement soft deletes by setting all attributes to NULL in the view when a profile is deleted.


4.3 Best practices for reliable incremental syncs

To avoid missing changes:

  • Ensure last_updated_at updates every time a synced column changes

  • Ensure last_updated_at reflects the most recent change across all synced columns — not just one of them. If your source table tracks update timestamps per field, compute last_updated_at in your view using the maximum across all relevant timestamps

  • Use a View if you need computed fields or type conversions

  • Index on last_updated_at for large tables


5) Test and enable your Sync

Before enabling the schedule:

  1. Run a test sync

  2. Verify:

    • Profiles are created or updated correctly

    • batch__, date__, and url__ fields are interpreted correctly

    • Null values behave as expected (null → attribute removal)

Once enabled, Batch automatically handles:

  • batching

  • retries

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