Sync data across multiple cloud and on-premises databases with SQL Data Sync (Preview)

SQL Data Sync is a service built on Azure SQL Database that lets you synchronize the data you select bi-directionally across multiple SQL databases and SQL Server instances.

Data Sync is based around the concept of a Sync Group. A Sync Group is a group of databases that you want to synchronize.

A Sync Group has the following properties:

  • The Sync Schema describes which data is being synchronized.

  • The Sync Direction can be bi-directional or can flow in only one direction. That is, the Sync Direction can be Hub to Member or Member to Hub, or both.

  • The Sync Interval is how often synchronization occurs.

  • The Conflict Resolution Policy is a group level policy, which can be Hub wins or Member wins.

Data Sync uses a hub and spoke topology to synchronize data. You define one of the databases in the group as the Hub Database. The rest of the databases are member databases. Sync occurs only between the Hub and individual members.

  • The Hub Database must be an Azure SQL Database.
  • The member databases can be either SQL Databases, on-premises SQL Server databases, or SQL Server instances on Azure virtual machines.
  • The Sync Database contains the metadata and log for Data Sync. The Sync Database has to be an Azure SQL Database located in the same region as the Hub Database. The Sync Database is customer created and customer owned.


If you're using an on premises database, you have to configure a local agent.

Sync data between databases

When to use Data Sync

Data Sync is useful in cases where data needs to be kept up to date across several Azure SQL Databases or SQL Server databases. Here are the main use cases for Data Sync:

  • Hybrid Data Synchronization: With Data Sync, you can keep data synchronized between your on-premises databases and Azure SQL Databases to enable hybrid applications. This capability may appeal to customers who are considering moving to the cloud and would like to put some of their application in Azure.

  • Distributed Applications: In many cases, it's beneficial to separate different workloads across different databases. For example, if you have a large production database, but you also need to run a reporting or analytics workload on this data, it's helpful to have a second database for this additional workload. This approach minimizes the performance impact on your production workload. You can use Data Sync to keep these two databases synchronized.

  • Globally Distributed Applications: Many businesses span several regions and even several countries. To minimize network latency, it's best to have your data in a region close to you. With Data Sync, you can easily keep databases in regions around the world synchronized.

Data Sync is not appropriate for the following scenarios:

  • Disaster Recovery

  • Read Scale

  • ETL (OLTP to OLAP)

  • Migration from on-premises SQL Server to Azure SQL Database

How does Data Sync work?

  • Tracking data changes: Data Sync tracks changes using insert, update, and delete triggers. The changes are recorded in a side table in the user database.

  • Synchronizing data: Data Sync is designed in a Hub and Spoke model. The Hub syncs with each member individually. Changes from the Hub are downloaded to the member and then changes from the member are uploaded to the Hub.

  • Resolving conflicts: Data Sync provides two options for conflict resolution, Hub wins or Member wins.

    • If you select Hub wins, the changes in the hub always overwrite changes in the member.
    • If you select Member wins, the changes in the member overwrite changes in the hub. If there's more than one member, the final value depends on which member syncs first.

Requirements and limitations

General considerations

Eventual consistency

Since Data Sync is trigger-based, transactional consistency is not guaranteed. Microsoft guarantees that all changes are made eventually and that Data Sync does not cause data loss.

Performance impact

Data Sync uses insert, update, and delete triggers to track changes. It creates side tables in the user database for change tracking. These change tracking activities have an impact on your database workload. Assess your service tier and upgrade if needed.

General requirements

  • Each table must have a primary key. Don't change the value of the primary key in any row. If you have to change a primary key value, delete the row and recreate it with the new primary key value.

  • Snapshot isolation must be enabled. For more info, see Snapshot Isolation in SQL Server.

General limitations

  • A table cannot have an identity column that is not the primary key.

  • The names of objects (databases, tables, and columns) cannot contain the printable characters period (.), left square bracket ([), or right square bracket (]).

  • Azure Active Directory authentication is not supported.

Unsupported data types

  • FileStream


  • XMLSchemaCollection (XML supported)

  • Cursor, Timestamp, Hierarchyid

Limitations on service and database dimensions

Dimensions Limit Workaround
Maximum number of sync groups any database can belong to. 5
Maximum number of endpoints in a single sync group 30 Create multiple sync groups
Maximum number of on-premises endpoints in a single sync group. 5 Create multiple sync groups
Database, table, schema, and column names 50 characters per name
Tables in a sync group 500 Create multiple sync groups
Columns in a table in a sync group 1000
Data row size on a table 24 Mb
Minimum sync interval 5 Minutes

FAQ about SQL Data Sync

How much does the SQL Data Sync (Preview) service cost?

During the Preview, there is no charge for the SQL Data Sync (Preview) service itself. However, you still accrue data transfer charges for data movement in and out of your SQL Database instance. For more info, see SQL Database pricing.

What regions support Data Sync?

SQL Data Sync (Preview) is available in all public cloud regions.

Is a SQL Database account required?

Yes. You must have a SQL Database account to host the Hub Database.

Can I use Data Sync to sync between SQL Server on-premises databases only?

Not directly. You can sync between SQL Server on-premises databases indirectly, however, by creating a Hub database in Azure, and then adding the on-premises databases to the sync group.

Can I use Data Sync to seed data from my production database to an empty database, and then keep them synchronized?

Yes. Create the schema manually in the new database by scripting it from the original. After you create the schema, add the tables to a sync group to copy the data and keep it synced.

Should I use SQL Data Sync to back up and restore my databases?

It is not recommended to use SQL Data Sync (Preview) to create a backup of your data. You cannot back up and restore to a specific point in time because SQL Data Sync (Preview) synchronizations are not versioned. Furthermore, SQL Data Sync (Preview) does not back up other SQL objects, such as stored procedures, and does not do the equivalent of a restore operation quickly.

For one recommended backup technique, see Copy an Azure SQL database.

Is collation supported in SQL Data Sync?

Yes. SQL Data Sync supports collation in the following scenarios:

  • If the selected sync schema tables are not already in your hub or member databases, then when you deploy the sync group, the service automatically creates the corresponding tables and columns with the collation settings selected in the empty destination databases.

  • If the tables to be synced already exist in both your hub and member databases, SQL Data Sync requires that the primary key columns have the same collation between hub and member databases to successfully deploy the sync group. There are no collation restrictions on columns other than the primary key columns.

Is federation supported in SQL Data Sync?

Federation Root Database can be used in the SQL Data Sync (Preview) Service without any limitation. You cannot add the Federated Database endpoint to the current version of SQL Data Sync (Preview).

Next steps

For more info about SQL Data Sync, see:

For more info about SQL Database, see: